diff --git a/package-lock.json b/package-lock.json
index 8af855f12..e469e94e1 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -28,7 +28,9 @@
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@@ -1133,6 +1143,240 @@
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+        "https://github.com/sponsors/ctavan"
+      ],
+      "license": "MIT",
+      "bin": {
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+      "version": "4.0.7",
+      "resolved": "https://registry.npmjs.org/eventemitter3/-/eventemitter3-4.0.7.tgz",
+      "integrity": "sha512-8guHBZCwKnFhYdHr2ysuRWErTwhoN2X8XELRlrRwpmfeY2jjuUN4taQMsULKUVo1K4DvZl+0pgfyoysHxvmvEw==",
+      "dev": true,
+      "license": "MIT"
+    },
     "node_modules/eventsource": {
       "version": "3.0.7",
       "resolved": "https://registry.npmjs.org/eventsource/-/eventsource-3.0.7.tgz",
@@ -3637,6 +3876,14 @@
         "express": ">= 4.11"
       }
     },
+    "node_modules/extended-eventsource": {
+      "version": "1.7.0",
+      "resolved": "https://registry.npmjs.org/extended-eventsource/-/extended-eventsource-1.7.0.tgz",
+      "integrity": "sha512-s8rtvZuYcKBpzytHb5g95cHbZ1J99WeMnV18oKc5wKoxkHzlzpPc/bNAm7Da2Db0BDw0CAu1z3LpH+7UsyzIpw==",
+      "dev": true,
+      "license": "MIT",
+      "optional": true
+    },
     "node_modules/external-editor": {
       "version": "3.1.0",
       "resolved": "https://registry.npmjs.org/external-editor/-/external-editor-3.1.0.tgz",
@@ -4641,6 +4888,19 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/is-network-error": {
+      "version": "1.3.1",
+      "resolved": "https://registry.npmjs.org/is-network-error/-/is-network-error-1.3.1.tgz",
+      "integrity": "sha512-6QCxa49rQbmUWLfk0nuGqzql9U8uaV2H6279bRErPBHe/109hCzsLUBUHfbEtvLIHBd6hyXbgedBSHevm43Edw==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=16"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
     "node_modules/is-number": {
       "version": "7.0.0",
       "resolved": "https://registry.npmjs.org/is-number/-/is-number-7.0.0.tgz",
@@ -4900,6 +5160,16 @@
         "url": "https://github.com/sponsors/panva"
       }
     },
+    "node_modules/js-tiktoken": {
+      "version": "1.0.21",
+      "resolved": "https://registry.npmjs.org/js-tiktoken/-/js-tiktoken-1.0.21.tgz",
+      "integrity": "sha512-biOj/6M5qdgx5TKjDnFT1ymSpM5tbd3ylwDtrQvFQSu0Z7bBYko2dF+W/aUkXUPuk6IVpRxk/3Q2sHOzGlS36g==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "base64-js": "^1.5.1"
+      }
+    },
     "node_modules/js-tokens": {
       "version": "9.0.1",
       "resolved": "https://registry.npmjs.org/js-tokens/-/js-tokens-9.0.1.tgz",
@@ -4972,6 +5242,88 @@
         "json-buffer": "3.0.1"
       }
     },
+    "node_modules/langchain": {
+      "version": "1.2.30",
+      "resolved": "https://registry.npmjs.org/langchain/-/langchain-1.2.30.tgz",
+      "integrity": "sha512-Ofsk7LTGvIkyy3uesv7hpyerpTghdjNpYFJfIxJRGGLjd+4JgTVkT/Ax6Cjg0F6doEuO7VRID0NK2QwmT3A/bg==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@langchain/langgraph": "^1.1.2",
+        "@langchain/langgraph-checkpoint": "^1.0.0",
+        "langsmith": ">=0.5.0 <1.0.0",
+        "uuid": "^11.1.0",
+        "zod": "^3.25.76 || ^4"
+      },
+      "engines": {
+        "node": ">=20"
+      },
+      "peerDependencies": {
+        "@langchain/core": "^1.1.31"
+      }
+    },
+    "node_modules/langsmith": {
+      "version": "0.5.7",
+      "resolved": "https://registry.npmjs.org/langsmith/-/langsmith-0.5.7.tgz",
+      "integrity": "sha512-FjYf2oBGMoSXnaT4SRaFguIiGJaonZ5VKWKJDPl9awLZjz2RkN29AcQWceecSINVzXzTvtRWPOjAWT+XggqNNg==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@types/uuid": "^10.0.0",
+        "chalk": "^5.6.2",
+        "console-table-printer": "^2.12.1",
+        "p-queue": "^6.6.2",
+        "semver": "^7.6.3",
+        "uuid": "^10.0.0"
+      },
+      "peerDependencies": {
+        "@opentelemetry/api": "*",
+        "@opentelemetry/exporter-trace-otlp-proto": "*",
+        "@opentelemetry/sdk-trace-base": "*",
+        "openai": "*"
+      },
+      "peerDependenciesMeta": {
+        "@opentelemetry/api": {
+          "optional": true
+        },
+        "@opentelemetry/exporter-trace-otlp-proto": {
+          "optional": true
+        },
+        "@opentelemetry/sdk-trace-base": {
+          "optional": true
+        },
+        "openai": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/langsmith/node_modules/chalk": {
+      "version": "5.6.2",
+      "resolved": "https://registry.npmjs.org/chalk/-/chalk-5.6.2.tgz",
+      "integrity": "sha512-7NzBL0rN6fMUW+f7A6Io4h40qQlG+xGmtMxfbnH/K7TAtt8JQWVQK+6g0UXKMeVJoyV5EkkNsErQ8pVD3bLHbA==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": "^12.17.0 || ^14.13 || >=16.0.0"
+      },
+      "funding": {
+        "url": "https://github.com/chalk/chalk?sponsor=1"
+      }
+    },
+    "node_modules/langsmith/node_modules/uuid": {
+      "version": "10.0.0",
+      "resolved": "https://registry.npmjs.org/uuid/-/uuid-10.0.0.tgz",
+      "integrity": "sha512-8XkAphELsDnEGrDxUOHB3RGvXz6TeuYSGEZBOjtTtPm2lwhGBjLgOzLHB63IUWfBpNucQjND6d3AOudO+H3RWQ==",
+      "dev": true,
+      "funding": [
+        "https://github.com/sponsors/broofa",
+        "https://github.com/sponsors/ctavan"
+      ],
+      "license": "MIT",
+      "bin": {
+        "uuid": "dist/bin/uuid"
+      }
+    },
     "node_modules/levn": {
       "version": "0.4.1",
       "resolved": "https://registry.npmjs.org/levn/-/levn-0.4.1.tgz",
@@ -5190,6 +5542,16 @@
       "resolved": "https://registry.npmjs.org/ms/-/ms-2.1.3.tgz",
       "integrity": "sha512-6FlzubTLZG3J2a/NVCAleEhjzq5oxgHyaCU9yYXvcLsvoVaHJq/s5xXI6/XXP6tz7R9xAOtHnSO/tXtF3WRTlA=="
     },
+    "node_modules/mustache": {
+      "version": "4.2.0",
+      "resolved": "https://registry.npmjs.org/mustache/-/mustache-4.2.0.tgz",
+      "integrity": "sha512-71ippSywq5Yb7/tVYyGbkBggbU8H3u5Rz56fH60jGFgr8uHwxs+aSKeqmluIVzM0m0kB7xQjKS6qPfd0b2ZoqQ==",
+      "dev": true,
+      "license": "MIT",
+      "bin": {
+        "mustache": "bin/mustache"
+      }
+    },
     "node_modules/mute-stream": {
       "version": "1.0.0",
       "resolved": "https://registry.npmjs.org/mute-stream/-/mute-stream-1.0.0.tgz",
@@ -5519,9 +5881,9 @@
       }
     },
     "node_modules/openai": {
-      "version": "5.23.2",
-      "resolved": "https://registry.npmjs.org/openai/-/openai-5.23.2.tgz",
-      "integrity": "sha512-MQBzmTulj+MM5O8SKEk/gL8a7s5mktS9zUtAkU257WjvobGc9nKcBuVwjyEEcb9SI8a8Y2G/mzn3vm9n1Jlleg==",
+      "version": "6.27.0",
+      "resolved": "https://registry.npmjs.org/openai/-/openai-6.27.0.tgz",
+      "integrity": "sha512-osTKySlrdYrLYTt0zjhY8yp0JUBmWDCN+Q+QxsV4xMQnnoVFpylgKGgxwN8sSdTNw0G4y+WUXs4eCMWpyDNWZQ==",
       "dev": true,
       "license": "Apache-2.0",
       "bin": {
@@ -5529,7 +5891,7 @@
       },
       "peerDependencies": {
         "ws": "^8.18.0",
-        "zod": "^3.23.8"
+        "zod": "^3.25 || ^4.0"
       },
       "peerDependenciesMeta": {
         "ws": {
@@ -5592,6 +5954,16 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/p-finally": {
+      "version": "1.0.0",
+      "resolved": "https://registry.npmjs.org/p-finally/-/p-finally-1.0.0.tgz",
+      "integrity": "sha512-LICb2p9CB7FS+0eR1oqWnHhp0FljGLZCWBE9aix0Uye9W8LTQPwMTYVGWQWIw9RdQiDg4+epXQODwIYJtSJaow==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=4"
+      }
+    },
     "node_modules/p-limit": {
       "version": "3.1.0",
       "resolved": "https://registry.npmjs.org/p-limit/-/p-limit-3.1.0.tgz",
@@ -5622,6 +5994,52 @@
         "url": "https://github.com/sponsors/sindresorhus"
       }
     },
+    "node_modules/p-queue": {
+      "version": "6.6.2",
+      "resolved": "https://registry.npmjs.org/p-queue/-/p-queue-6.6.2.tgz",
+      "integrity": "sha512-RwFpb72c/BhQLEXIZ5K2e+AhgNVmIejGlTgiB9MzZ0e93GRvqZ7uSi0dvRF7/XIXDeNkra2fNHBxTyPDGySpjQ==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "eventemitter3": "^4.0.4",
+        "p-timeout": "^3.2.0"
+      },
+      "engines": {
+        "node": ">=8"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
+    "node_modules/p-retry": {
+      "version": "7.1.1",
+      "resolved": "https://registry.npmjs.org/p-retry/-/p-retry-7.1.1.tgz",
+      "integrity": "sha512-J5ApzjyRkkf601HpEeykoiCvzHQjWxPAHhyjFcEUP2SWq0+35NKh8TLhpLw+Dkq5TZBFvUM6UigdE9hIVYTl5w==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "is-network-error": "^1.1.0"
+      },
+      "engines": {
+        "node": ">=20"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
+    "node_modules/p-timeout": {
+      "version": "3.2.0",
+      "resolved": "https://registry.npmjs.org/p-timeout/-/p-timeout-3.2.0.tgz",
+      "integrity": "sha512-rhIwUycgwwKcP9yTOOFK/AKsAopjjCakVqLHePO3CC6Mir1Z99xT+R63jZxAT5lFZLa2inS5h+ZS2GvR99/FBg==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "p-finally": "^1.0.0"
+      },
+      "engines": {
+        "node": ">=8"
+      }
+    },
     "node_modules/package-json-from-dist": {
       "version": "1.0.1",
       "resolved": "https://registry.npmjs.org/package-json-from-dist/-/package-json-from-dist-1.0.1.tgz",
@@ -6433,6 +6851,13 @@
         "url": "https://github.com/sponsors/isaacs"
       }
     },
+    "node_modules/simple-wcswidth": {
+      "version": "1.1.2",
+      "resolved": "https://registry.npmjs.org/simple-wcswidth/-/simple-wcswidth-1.1.2.tgz",
+      "integrity": "sha512-j7piyCjAeTDSjzTSQ7DokZtMNwNlEAyxqSZeCS+CXH7fJ4jx3FuJ/mTW3mE+6JLs4VJBbcll0Kjn+KXI5t21Iw==",
+      "dev": true,
+      "license": "MIT"
+    },
     "node_modules/source-map-js": {
       "version": "1.2.1",
       "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz",
@@ -7704,6 +8129,20 @@
         "punycode": "^2.1.0"
       }
     },
+    "node_modules/uuid": {
+      "version": "11.1.0",
+      "resolved": "https://registry.npmjs.org/uuid/-/uuid-11.1.0.tgz",
+      "integrity": "sha512-0/A9rDy9P7cJ+8w1c9WD9V//9Wj15Ce2MPz8Ri6032usz+NfePxx5AcN3bN+r6ZL6jEo066/yNYB3tn4pQEx+A==",
+      "dev": true,
+      "funding": [
+        "https://github.com/sponsors/broofa",
+        "https://github.com/sponsors/ctavan"
+      ],
+      "license": "MIT",
+      "bin": {
+        "uuid": "dist/esm/bin/uuid"
+      }
+    },
     "node_modules/validate-npm-package-license": {
       "version": "3.0.4",
       "resolved": "https://registry.npmjs.org/validate-npm-package-license/-/validate-npm-package-license-3.0.4.tgz",
@@ -8156,28 +8595,6 @@
       "resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz",
       "integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ=="
     },
-    "node_modules/ws": {
-      "version": "8.18.3",
-      "resolved": "https://registry.npmjs.org/ws/-/ws-8.18.3.tgz",
-      "integrity": "sha512-PEIGCY5tSlUt50cqyMXfCzX+oOPqN0vuGqWzbcJ2xvnkzkq46oOpz7dQaTDBdfICb4N14+GARUDw2XV2N4tvzg==",
-      "dev": true,
-      "license": "MIT",
-      "engines": {
-        "node": ">=10.0.0"
-      },
-      "peerDependencies": {
-        "bufferutil": "^4.0.1",
-        "utf-8-validate": ">=5.0.2"
-      },
-      "peerDependenciesMeta": {
-        "bufferutil": {
-          "optional": true
-        },
-        "utf-8-validate": {
-          "optional": true
-        }
-      }
-    },
     "node_modules/yocto-queue": {
       "version": "0.1.0",
       "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
diff --git a/package.json b/package.json
index 522a8bb6e..0f0e6995f 100644
--- a/package.json
+++ b/package.json
@@ -43,7 +43,7 @@
     "build:inspect:docker:http": "run-s build:docker inspect:docker:http",
     "test": "vitest --config ./vitest.config.ts",
     "test:e2e": "vitest --config ./vitest.config.e2e.ts",
-    "test:eval": "vitest --config ./vitest.config.eval.ts",
+    "test:eval": "tsx tests/eval/runEval.ts",
     "test:oauth:embedded": "vitest --config ./vitest.config.oauth.embedded.ts",
     "coverage": "vitest run --config ./vitest.config.ts --coverage",
     "version:major": "npm version major --no-git-tag-version",
@@ -68,7 +68,9 @@
     "@anthropic-ai/mcpb": "^1.0.0",
     "@eslint/eslintrc": "^3.3.1",
     "@eslint/js": "^9.25.1",
-    "@openai/agents": "^0.1.9",
+    "@langchain/core": "^1.1.31",
+    "@langchain/mcp-adapters": "^1.1.3",
+    "@langchain/openai": "^1.2.12",
     "@types/cors": "^2.8.19",
     "@types/eslint__js": "^8.42.3",
     "@types/express": "^5.0.3",
@@ -83,8 +85,9 @@
     "eslint-config-prettier": "^10.1.2",
     "eslint-plugin-prettier": "^5.2.6",
     "eslint-plugin-simple-import-sort": "^12.1.1",
+    "langchain": "^1.2.30",
+    "langsmith": "^0.5.7",
     "npm-run-all": "^4.1.5",
-    "openai": "^5.23.2",
     "prettier": "^3.5.3",
     "supertest": "^7.1.4",
     "tsx": "^4.21.0",
diff --git a/tests/eval/base.ts b/tests/eval/base.ts
index a1a4ff0a3..2176da96b 100644
--- a/tests/eval/base.ts
+++ b/tests/eval/base.ts
@@ -1,27 +1,13 @@
-import { CallToolResultSchema } from '@modelcontextprotocol/sdk/types.js';
-import {
-  Agent,
-  getAllMcpTools,
-  MCPServerStdio,
-  OpenAIChatCompletionsModel,
-  StreamedRunResult,
-  withTrace,
-} from '@openai/agents';
-import { OpenAI } from 'openai/client.js';
-import { Err, Ok, Result } from 'ts-results-es';
-import z from 'zod';
-
-import invariant from '../../src/utils/invariant.js';
-
-type ToolExecution = {
-  name: string;
-  arguments: Record<string, unknown>;
-  output: string;
-};
+import { MultiServerMCPClient, StdioConnection } from '@langchain/mcp-adapters';
+import { ChatOpenAI } from '@langchain/openai';
+import { AIMessage, createAgent, HumanMessage, SystemMessage, ToolMessage } from 'langchain';
 
 const DEFAULT_MODEL = 'claude-sonnet-4-5-20250929';
 
-function getApiKey(): string {
+type Message = AIMessage | HumanMessage | SystemMessage | ToolMessage;
+type Agent = ReturnType<typeof createAgent>;
+
+export function getApiKey(): string {
   const { OPENAI_API_KEY } = process.env;
 
   if (!OPENAI_API_KEY) {
@@ -35,125 +21,64 @@ export function getModel(): string {
   return process.env.EVAL_TEST_MODEL || DEFAULT_MODEL;
 }
 
-export async function getMcpServer(env?: Record<string, string>): Promise<MCPServerStdio> {
-  const mcpServer = new MCPServerStdio({
+export function getMcpServer(env?: Record<string, string>): StdioConnection {
+  const mcpServer: StdioConnection = {
     command: 'node',
     args: ['build/index.js'],
     env,
-    cacheToolsList: true,
-  });
+  };
 
-  await mcpServer.connect();
   return mcpServer;
 }
 
 export async function getAgent({
-  systemPrompt,
   model,
   mcpServer,
 }: {
-  systemPrompt: string;
   model: string;
-  mcpServer?: MCPServerStdio;
-}): Promise<Agent> {
-  return await withTrace('get_agent', async () => {
-    const agentOptions = {
-      name: 'Assistant with Tableau MCP tools',
-      instructions: systemPrompt,
-      model: new OpenAIChatCompletionsModel(
-        new OpenAI({
-          baseURL: process.env.OPENAI_BASE_URL,
-          apiKey: getApiKey(),
-        }),
-        model,
-      ),
-    };
-
-    if (!mcpServer) {
-      return new Agent(agentOptions);
-    }
-
-    const tools = await getAllMcpTools([mcpServer]);
-    tools.forEach((tool) => {
-      tool.name = `tableau_${tool.name}`;
-    });
-
-    return new Agent({
-      ...agentOptions,
-      mcpServers: [mcpServer],
-      tools,
-      modelSettings: { toolChoice: 'required' },
-    });
+  mcpServer?: StdioConnection;
+}): Promise<{ agent: Agent; client?: MultiServerMCPClient }> {
+  const agentOptions = {
+    name: 'Assistant with Tableau MCP tools',
+    model: new ChatOpenAI({
+      model,
+      configuration: {
+        apiKey: getApiKey(),
+        baseURL: process.env.OPENAI_BASE_URL,
+      },
+    }),
+  };
+
+  if (!mcpServer) {
+    return { agent: createAgent({ ...agentOptions }) };
+  }
+
+  const client = new MultiServerMCPClient({
+    tableau: mcpServer,
   });
-}
 
-export async function getToolExecutions(
-  result: StreamedRunResult<undefined, any>,
-): Promise<Array<ToolExecution>> {
-  const toolExecutions: Map<string, ToolExecution> = new Map();
-
-  for (const item of result.history) {
-    if (item.type === 'function_call') {
-      toolExecutions.set(item.callId, {
-        name: item.name,
-        arguments: JSON.parse(item.arguments) as Record<string, unknown>,
-        output: '',
-      });
-    }
-  }
+  const tools = await client.getTools();
+  return {
+    agent: createAgent({ ...agentOptions, tools }),
+    client,
+  };
+}
 
-  for (const item of result.history) {
-    if (item.type === 'function_call_result') {
-      const call = toolExecutions.get(item.callId);
-      if (!call) {
-        throw new Error(`Could not find tool execution for callId ${item.callId}`);
-      }
-
-      call.output =
-        item.output.type === 'text'
-          ? item.output.text
-          : item.output.type === 'image'
-            ? item.output.data
-            : '';
-    }
-  }
+export async function prompt(agent: Agent, content: string): Promise<Array<Message>> {
+  console.log(`Invoking agent with input: ${content}...`);
 
-  log('🛠️ tool executions:');
-  const executions = [...toolExecutions.values()];
-  for (const execution of executions) {
-    log(`  🔨 ${execution.name}`);
-    log(`    👉 arguments: ${JSON.stringify(execution.arguments)}`);
-    log(`    👈 output: ${execution.output}`);
-    log('\n');
-  }
+  const start = performance.now();
 
-  return executions;
-}
+  const { messages } = (await agent.invoke({
+    messages: [{ role: 'user', content }],
+  })) as { messages: Array<Message> };
 
-export function getCallToolResult<Z extends z.ZodTypeAny = z.ZodNever>(
-  toolExecution: ToolExecution,
-  schema: Z,
-): z.infer<Z> {
-  const callToolResult = CallToolResultSchema.parse(JSON.parse(toolExecution.output));
-  invariant(callToolResult.type === 'text');
-  invariant(typeof callToolResult.text === 'string');
-  const result = schema.parse(JSON.parse(callToolResult.text));
-  return result;
-}
+  const end = performance.now();
 
-export function getCallToolResultSafe<Z extends z.ZodTypeAny = z.ZodNever>(
-  toolExecution: ToolExecution,
-  schema: Z,
-): Result<z.infer<Z>, Error> {
-  const callToolResult = CallToolResultSchema.safeParse(JSON.parse(toolExecution.output));
-  if (!callToolResult.success) {
-    return Err(callToolResult.error);
-  }
+  const duration = Math.round(end - start);
+  console.log(`Agent response received after ${duration}ms`);
 
-  invariant(callToolResult.data.type === 'text');
-  invariant(typeof callToolResult.data.text === 'string');
-  const result = schema.parse(JSON.parse(callToolResult.data.text));
-  return Ok(result);
+  return messages;
 }
 
 export function log(message?: any, force?: boolean): void {
diff --git a/tests/eval/ensureDatasetExists.ts b/tests/eval/ensureDatasetExists.ts
new file mode 100644
index 000000000..443d85627
--- /dev/null
+++ b/tests/eval/ensureDatasetExists.ts
@@ -0,0 +1,119 @@
+import { Client } from 'langsmith';
+import { ExampleCreate } from 'langsmith/schemas';
+
+import { evalInputSchema, evalReferenceSchema } from './evaluators';
+import { EvalExample, examples } from './examples';
+
+export async function ensureDatasetExists({
+  client,
+  datasetName,
+  datasetDescription,
+}: {
+  client: Client;
+  datasetName: string;
+  datasetDescription: string;
+}): Promise<void> {
+  console.log(`Ensuring dataset "${datasetName}" exists`);
+  console.log('Getting current datasets...');
+  const datasets = client.listDatasets({ datasetName });
+
+  let dataset = await first(datasets);
+
+  if (dataset) {
+    console.log(`Dataset "${datasetName}" already exists`);
+  } else {
+    console.log(`Creating dataset "${datasetName}"...`);
+    dataset = await client.createDataset(datasetName, {
+      description: datasetDescription,
+    });
+    console.log(`Created dataset "${datasetName}"`);
+  }
+
+  console.log('Getting current examples...');
+  const datasetExamples = await toArray(client.listExamples({ datasetId: dataset.id }));
+
+  const datasetExamplesStr = datasetExamples.length === 1 ? 'example' : 'examples';
+  console.log(`Found ${datasetExamples.length} ${datasetExamplesStr} in dataset`);
+
+  const missingExamples: Array<EvalExample> = examples.filter((example) => {
+    return !datasetExamples.some((e) => e.inputs.question === example.inputs.question);
+  });
+
+  const mismatchedExamples: Array<EvalExample> = [];
+  for (const datasetExample of datasetExamples) {
+    const inputResult = evalInputSchema.safeParse(datasetExample.inputs);
+    if (!inputResult.success) {
+      console.log("Dataset example inputs don't match expected schema");
+      console.log(`Deleting example: ${datasetExample.id}...`);
+      await client.deleteExample(datasetExample.id);
+      continue;
+    }
+
+    const datasetInputs = inputResult.data;
+    const example = examples.find((e) => e.inputs.question === datasetInputs.question);
+    if (!example) {
+      console.log(`Dataset example not found: ${datasetInputs.question}`);
+      console.log(`Deleting example: ${datasetExample.id}...`);
+      await client.deleteExample(datasetExample.id);
+      continue;
+    }
+
+    const outputResult = evalReferenceSchema.safeParse(datasetExample.outputs);
+    if (!outputResult.success) {
+      console.log(`Example outputs don't match expected schema: ${datasetExample.inputs.question}`);
+      console.log(`Deleting example: ${datasetExample.id}...`);
+      await client.deleteExample(datasetExample.id);
+      mismatchedExamples.push(example);
+      continue;
+    }
+
+    const datasetOutputs = outputResult.data;
+    if (
+      datasetOutputs.rubric !== example.outputs.rubric ||
+      datasetOutputs.mustContain.length !== example.outputs.mustContain.length ||
+      !datasetOutputs.mustContain.every((mustContain) =>
+        example.outputs.mustContain.includes(mustContain),
+      ) ||
+      datasetOutputs.expectedTools.length !== example.outputs.expectedTools.length ||
+      !datasetOutputs.expectedTools.every((tool) => example.outputs.expectedTools.includes(tool))
+    ) {
+      console.log(`Example mismatch: ${datasetExample.inputs.question}`);
+      console.log('Deleting example...');
+      await client.deleteExample(datasetExample.id);
+      mismatchedExamples.push(example);
+    }
+  }
+
+  const uploads: Array<ExampleCreate> = [...missingExamples, ...mismatchedExamples].map(
+    (example) => ({
+      inputs: example.inputs,
+      outputs: example.outputs,
+      dataset_id: dataset.id,
+    }),
+  );
+
+  if (uploads.length === 0) {
+    console.log('Dataset examples are up to date');
+    return;
+  }
+
+  const examplesStr = uploads.length === 1 ? 'example' : 'examples';
+  console.log(`Creating ${uploads.length} ${examplesStr}...`);
+  await client.createExamples(uploads);
+  console.log(`Created ${uploads.length} ${examplesStr}`);
+}
+
+async function first<T>(iter: AsyncIterable<T>): Promise<T | undefined> {
+  for await (const item of iter) {
+    return item;
+  }
+}
+
+async function toArray<T>(iter: AsyncIterable<T>): Promise<T[]> {
+  const result: Array<T> = [];
+  for await (const item of iter) {
+    result.push(item);
+  }
+
+  return result;
+}
diff --git a/tests/eval/evaluationResult.ts b/tests/eval/evaluationResult.ts
deleted file mode 100644
index e79390c62..000000000
--- a/tests/eval/evaluationResult.ts
+++ /dev/null
@@ -1,10 +0,0 @@
-import z from 'zod';
-
-export const evaluationSchema = z.object({
-  accuracy: z.number(),
-  completeness: z.number(),
-  relevance: z.number(),
-  clarity: z.number(),
-  reasoning: z.number(),
-  comments: z.string(),
-});
diff --git a/tests/eval/evaluators.ts b/tests/eval/evaluators.ts
new file mode 100644
index 000000000..0bc96b067
--- /dev/null
+++ b/tests/eval/evaluators.ts
@@ -0,0 +1,134 @@
+import { AIMessage } from 'langchain';
+import { EvaluationResult, EvaluatorT } from 'langsmith/evaluation';
+import { KVMap } from 'langsmith/schemas';
+import z from 'zod';
+
+import { getAgent, getModel, prompt } from './base';
+
+export const evalInputSchema = z.object({
+  question: z.string(),
+});
+
+export const evalOutputSchema = z.object({
+  toolsUsed: z.array(
+    z.object({
+      name: z.string(),
+      content: z.string(),
+    }),
+  ),
+});
+
+export const evalReferenceSchema = z.object({
+  expectedTools: z.array(z.string()),
+  mustContain: z.array(z.string()),
+  rubric: z.string(),
+});
+
+export type EvalInput = z.infer<typeof evalInputSchema>;
+export type EvalOutput = z.infer<typeof evalOutputSchema>;
+export type EvalReference = z.infer<typeof evalReferenceSchema>;
+
+/** Checks that every expected tool was actually invoked */
+export const toolSelectionGrader: EvaluatorT = async ({
+  outputs,
+  referenceOutputs,
+}: {
+  outputs: KVMap;
+  referenceOutputs?: KVMap;
+}): Promise<EvaluationResult> => {
+  const { toolsUsed } = evalOutputSchema.parse(outputs);
+  const { expectedTools } = evalReferenceSchema.parse(referenceOutputs ?? { expectedTools: [] });
+
+  if (expectedTools.length === 0) {
+    return { key: 'tool_selection', score: 1 };
+  }
+
+  const hits = expectedTools.filter((expectedTool) =>
+    toolsUsed.some((actualTool) => actualTool.name === expectedTool),
+  );
+
+  const score = hits.length / expectedTools.length;
+
+  return {
+    key: 'tool_selection',
+    score,
+    comment: `Expected [${expectedTools.join(', ')}] - got [${toolsUsed.map((tool) => tool.name).join(', ')}]`,
+  };
+};
+
+/** Checks that the output contains required substrings */
+export const contentPresenceGrader: EvaluatorT = async ({
+  outputs,
+  referenceOutputs,
+}: {
+  outputs: KVMap;
+  referenceOutputs?: KVMap;
+}): Promise<EvaluationResult> => {
+  const { toolsUsed } = evalOutputSchema.parse(outputs);
+  const { mustContain } = evalReferenceSchema.parse(referenceOutputs ?? { mustContain: [] });
+
+  if (mustContain.length === 0) {
+    return { key: 'content_presence', score: 1 };
+  }
+
+  const hits = toolsUsed.filter((tool) =>
+    mustContain.some((s) => tool.content.toLowerCase().includes(s.toLowerCase())),
+  );
+  const score = hits.length / mustContain.length;
+
+  return {
+    key: 'content_presence',
+    score,
+    comment: `Found ${hits.length}/${mustContain.length} required terms`,
+  };
+};
+
+/** LLM-as-judge for open-ended rubric grading */
+export const rubricGrader: EvaluatorT = async ({
+  inputs,
+  outputs,
+  referenceOutputs,
+}: {
+  inputs: KVMap;
+  outputs: KVMap;
+  referenceOutputs?: KVMap;
+}): Promise<EvaluationResult> => {
+  const { question } = evalInputSchema.parse(inputs);
+  const { toolsUsed } = evalOutputSchema.parse(outputs);
+  const { rubric } = evalReferenceSchema.parse(referenceOutputs ?? { rubric: '' });
+
+  if (!rubric) {
+    return { key: 'rubric', score: 1 };
+  }
+
+  const judgePrompt = `You are evaluating an AI agent's response to a user question.
+
+Question: ${question}
+Agent Response: ${toolsUsed.map((tool) => tool.content).join('\n') || 'none'}
+Tools Used: ${toolsUsed.map((tool) => tool.name).join(', ') || 'none'}
+
+Rubric: ${rubric}
+
+Score the response from 0.0 to 1.0.
+Respond ONLY with JSON: {"score": <number>, "comment": "<brief reason>"}`;
+
+  const { agent } = await getAgent({
+    model: getModel(),
+  });
+
+  const messages = await prompt(agent, judgePrompt);
+
+  const text =
+    messages.find<AIMessage>((message) => AIMessage.isInstance(message))?.content?.toString() ?? '';
+
+  try {
+    const parsed = JSON.parse(text.replace(/```json|```/g, '').trim());
+    return {
+      key: 'rubric',
+      score: parsed.score,
+      comment: parsed.comment,
+    };
+  } catch {
+    return { key: 'rubric', score: 0, comment: 'Judge failed to parse' };
+  }
+};
diff --git a/tests/eval/examples.ts b/tests/eval/examples.ts
new file mode 100644
index 000000000..c0bc9a2aa
--- /dev/null
+++ b/tests/eval/examples.ts
@@ -0,0 +1,18 @@
+import { EvalInput, EvalReference } from './evaluators';
+
+export type EvalExample = {
+  inputs: EvalInput;
+  outputs: EvalReference;
+};
+
+export const examples: Array<EvalExample> = [
+  {
+    inputs: { question: 'Show me my datasources' },
+    outputs: {
+      expectedTools: ['list-datasources'],
+      mustContain: ['Superstore Datasource'],
+      rubric:
+        'Response should list datasource names and luid values. A JSON blob should be returned.',
+    },
+  },
+];
diff --git a/tests/eval/getDatasourceMetadata.test.ts b/tests/eval/getDatasourceMetadata.test.ts
deleted file mode 100644
index 6f60d4e89..000000000
--- a/tests/eval/getDatasourceMetadata.test.ts
+++ /dev/null
@@ -1,102 +0,0 @@
-import { MCPServerStdio } from '@openai/agents';
-import dotenv from 'dotenv';
-import z from 'zod';
-
-import { dataSourceSchema } from '../../src/sdks/tableau/types/dataSource.js';
-import { fieldsResultSchema } from '../../src/tools/getDatasourceMetadata/datasourceMetadataUtils.js';
-import invariant from '../../src/utils/invariant.js';
-import { Datasource } from '../constants.js';
-import { getDefaultEnv, getSuperstoreDatasource, resetEnv, setEnv } from '../testEnv.js';
-import {
-  getCallToolResult,
-  getCallToolResultSafe,
-  getMcpServer,
-  getModel,
-  getToolExecutions,
-} from './base.js';
-import { grade } from './grade.js';
-
-describe('get-datasource-metadata', () => {
-  let mcpServer: MCPServerStdio;
-  let superstore: Datasource;
-
-  beforeAll(setEnv);
-  afterAll(resetEnv);
-
-  beforeAll(async () => {
-    dotenv.config({ path: 'tests/eval/.env' });
-  });
-
-  beforeEach(async () => {
-    const env = getDefaultEnv();
-    superstore = getSuperstoreDatasource(env);
-    mcpServer = await getMcpServer(env);
-  });
-
-  afterEach(async () => {
-    await mcpServer.close();
-  });
-
-  it('should call get_datasource_metadata tool', async () => {
-    const prompt =
-      'For the Superstore data source, get its metadata. Do not perform any analysis on the metadata, just show it.';
-
-    const { agentResult } = await grade({
-      mcpServer,
-      model: getModel(),
-      prompt,
-    });
-
-    const toolExecutions = await getToolExecutions(agentResult);
-    expect(toolExecutions.length).toBeGreaterThanOrEqual(2);
-
-    const listDatasourcesToolExecution = toolExecutions.find((toolExecution) => {
-      if (toolExecution.name !== 'list_datasources') {
-        return false;
-      }
-
-      const result = getCallToolResultSafe(toolExecution, z.array(dataSourceSchema));
-      if (result.isErr()) {
-        return false;
-      }
-
-      if (result.value.length === 0) {
-        return false;
-      }
-
-      return true;
-    });
-
-    invariant(listDatasourcesToolExecution, 'list_datasources tool execution not found');
-
-    const datasources = getCallToolResult(listDatasourcesToolExecution, z.array(dataSourceSchema));
-    expect(datasources.length).greaterThan(0);
-    const datasource = datasources.find(
-      (datasource) => datasource.name === 'Superstore Datasource',
-    );
-
-    expect(datasource).toMatchObject({
-      id: superstore.id,
-      name: 'Superstore Datasource',
-    });
-
-    const getDatasourceMetadataToolExecution = toolExecutions.find((toolExecution) => {
-      return (
-        toolExecution.name === 'get_datasource_metadata' &&
-        toolExecution.arguments.datasourceLuid === superstore.id
-      );
-    });
-
-    invariant(
-      getDatasourceMetadataToolExecution,
-      'get_datasource_metadata tool execution not found',
-    );
-
-    const { fields } = getCallToolResult(getDatasourceMetadataToolExecution, fieldsResultSchema);
-    expect(fields.length).toBeGreaterThan(0);
-
-    const fieldNames = fields.map((field) => field.name);
-    expect(fieldNames).toContain('Postal Code');
-    expect(fieldNames).toContain('Product Name');
-  });
-});
diff --git a/tests/eval/grade.ts b/tests/eval/grade.ts
deleted file mode 100644
index 4dfd32170..000000000
--- a/tests/eval/grade.ts
+++ /dev/null
@@ -1,113 +0,0 @@
-import { MCPServerStdio, run, StreamedRunResult, withTrace } from '@openai/agents';
-
-import { getAgent, log } from './base.js';
-import { evaluationSchema } from './evaluationResult.js';
-
-type GradeInput = {
-  mcpServer: MCPServerStdio;
-  model: string;
-  prompt: string;
-};
-
-const agentSystemPrompt = `
-  You are an assistant responsible for evaluating the results of calling various tools.
-  Given the user's query, use the tools available to you to answer the question.`;
-
-const evalSystemPrompt = `
-  You are an expert evaluator assessing how well an LLM answers a given question.
-  Review the provided answer and score it from 1 to 5 in each of the following categories:
-    Accuracy - Does the answer contain factual errors or hallucinations?
-    Completeness - Does the answer fully address all parts of the question?
-    Relevance - Is the information directly related to the question?
-    Clarity - Is the explanation easy to understand and well-structured?
-    Reasoning - Does the answer show logical thinking or provide evidence or rationale?
-    Return your evaluation as a JSON object in the format:
-    {
-        "accuracy": 1-5,
-        "completeness": 1-5,
-        "relevance": 1-5,
-        "clarity": 1-5,
-        "reasoning": 1-5,
-        "comments": "A short paragraph summarizing the strengths and weaknesses of the answer."
-    }`;
-
-export async function grade({
-  mcpServer,
-  model,
-  prompt,
-}: GradeInput): Promise<{ agentResult: StreamedRunResult<any, any> }> {
-  const evals = await promptAgent({ mcpServer, model, prompt });
-  log('\n');
-
-  const evalAgentPrompt = `
-    Here is the user input: ${prompt}
-    Here is the LLM's answer: ${evals.finalOutput}`;
-
-  const evalAgent = await getAgent({
-    model,
-    systemPrompt: evalSystemPrompt,
-  });
-
-  const result = await withTrace('run_eval_agent', async () => {
-    const stream = await run(evalAgent, evalAgentPrompt, { stream: true });
-    if (process.env.ENABLE_LOGGING === 'true') {
-      stream.toTextStream({ compatibleWithNodeStreams: true }).pipe(process.stdout);
-    }
-
-    await stream.completed;
-    return stream;
-  });
-
-  log('\n');
-
-  const jsonRegexes = [/(?<JSON>\{[^}]+\})/];
-  for (const jsonRegex of jsonRegexes) {
-    const match = result.finalOutput?.match(jsonRegex);
-    if (match) {
-      const evaluationResult = evaluationSchema.safeParse(JSON.parse(match.groups?.JSON ?? '{}'));
-      if (!evaluationResult.success) {
-        throw new Error(
-          `Could not parse agent output as an evaluation result:\n${result.finalOutput}`,
-        );
-      }
-
-      const evaluation = evaluationResult.data;
-      expect(evaluation.accuracy).toBeGreaterThanOrEqual(4);
-      expect(evaluation.completeness).toBeGreaterThanOrEqual(4);
-      expect(evaluation.relevance).toBeGreaterThanOrEqual(4);
-      expect(evaluation.clarity).toBeGreaterThanOrEqual(4);
-      expect(evaluation.reasoning).toBeGreaterThanOrEqual(4);
-
-      return {
-        agentResult: evals,
-      };
-    }
-  }
-  throw new Error('Could not parse JSON from agent output');
-}
-
-async function promptAgent({
-  mcpServer,
-  model,
-  prompt,
-}: GradeInput): Promise<StreamedRunResult<any, any>> {
-  log(`Evaluating prompt: ${prompt}`, true);
-
-  const agentWithTools = await getAgent({
-    mcpServer,
-    model,
-    systemPrompt: agentSystemPrompt,
-  });
-
-  const result = await withTrace('run_agent_with_tools', async () => {
-    const stream = await run(agentWithTools, prompt, { stream: true });
-    if (process.env.ENABLE_LOGGING === 'true') {
-      stream.toTextStream({ compatibleWithNodeStreams: true }).pipe(process.stdout);
-    }
-
-    await stream.completed;
-    return stream;
-  });
-
-  return result;
-}
diff --git a/tests/eval/listDatasources.test.ts b/tests/eval/listDatasources.test.ts
deleted file mode 100644
index c09a2cf09..000000000
--- a/tests/eval/listDatasources.test.ts
+++ /dev/null
@@ -1,59 +0,0 @@
-import { MCPServerStdio } from '@openai/agents';
-import dotenv from 'dotenv';
-import z from 'zod';
-
-import { dataSourceSchema } from '../../src/sdks/tableau/types/dataSource.js';
-import { Datasource } from '../constants.js';
-import { getDefaultEnv, getSuperstoreDatasource, resetEnv, setEnv } from '../testEnv.js';
-import { getCallToolResult, getMcpServer, getModel, getToolExecutions } from './base.js';
-import { grade } from './grade.js';
-
-describe('list-datasources', () => {
-  let mcpServer: MCPServerStdio;
-  let superstore: Datasource;
-
-  beforeAll(setEnv);
-  afterAll(resetEnv);
-
-  beforeAll(async () => {
-    dotenv.config({ path: 'tests/eval/.env' });
-  });
-
-  beforeEach(async () => {
-    const env = getDefaultEnv();
-    superstore = getSuperstoreDatasource(env);
-    mcpServer = await getMcpServer(env);
-  });
-
-  afterEach(async () => {
-    await mcpServer?.close();
-  });
-
-  it('should call list_datasources tool', async () => {
-    const prompt =
-      'List the data sources that are available on my Tableau site. Do not perform any analysis on the the list of data sources, just show the list.';
-
-    const { agentResult } = await grade({
-      mcpServer,
-      model: getModel(),
-      prompt,
-    });
-
-    const toolExecutions = await getToolExecutions(agentResult);
-
-    expect(toolExecutions.length).toBe(1);
-    expect(toolExecutions[0].name).toBe('list_datasources');
-    expect(toolExecutions[0].arguments.filter).toBeFalsy();
-
-    const datasources = getCallToolResult(toolExecutions[0], z.array(dataSourceSchema));
-    expect(datasources.length).greaterThan(0);
-    const datasource = datasources.find(
-      (datasource) => datasource.name === 'Superstore Datasource',
-    );
-
-    expect(datasource).toMatchObject({
-      id: superstore.id,
-      name: 'Superstore Datasource',
-    });
-  });
-});
diff --git a/tests/eval/runEval.ts b/tests/eval/runEval.ts
new file mode 100644
index 000000000..e13189cc8
--- /dev/null
+++ b/tests/eval/runEval.ts
@@ -0,0 +1,70 @@
+import dotenv from 'dotenv';
+import { Client } from 'langsmith';
+import { evaluate, type EvaluateOptions } from 'langsmith/evaluation';
+
+import { setEnv } from '../testEnv';
+import { ensureDatasetExists } from './ensureDatasetExists';
+import {
+  contentPresenceGrader,
+  evalInputSchema,
+  rubricGrader,
+  toolSelectionGrader,
+} from './evaluators';
+import { target } from './target';
+
+async function runEval(): Promise<void> {
+  setEnv();
+  dotenv.config({ path: 'tests/eval/.env' });
+
+  const client = new Client();
+
+  const datasetName = 'Tableau MCP: Development';
+  await ensureDatasetExists({
+    client,
+    datasetName,
+    datasetDescription: 'Tableau MCP evaluation dataset',
+  });
+
+  console.log('\n🚀 Starting evaluation run...\n');
+
+  const options: EvaluateOptions = {
+    data: datasetName,
+    evaluators: [toolSelectionGrader, contentPresenceGrader, rubricGrader],
+    experimentPrefix: 'tableau-mcp',
+    maxConcurrency: 2,
+  };
+
+  const { results } = await evaluate(target, options);
+
+  // Print summary
+  console.log('\n📊 Results Summary\n' + '-'.repeat(50));
+
+  const scores: Record<string, number[]> = {};
+
+  for await (const result of results) {
+    const { question } = evalInputSchema.parse(result.example.inputs);
+    console.log(`\n🔹 "${question}"`);
+
+    for (const evalResult of result.evaluationResults.results) {
+      const { key, score, comment } = evalResult;
+
+      const numScore = typeof score === 'number' ? score : null;
+      const pct = numScore != null ? `${(numScore * 100).toFixed(0)}%` : 'N/A';
+      console.log(`   ${key}: ${pct}${comment ? ` - ${comment}` : ''}`);
+
+      if (numScore !== null) {
+        scores[key] = [...(scores[key] ?? []), numScore];
+      }
+    }
+  }
+
+  console.log('\n📈 Aggregate Scores\n' + '-'.repeat(50));
+  for (const [key, vals] of Object.entries(scores)) {
+    const avg = vals.reduce((a, b) => a + b, 0) / vals.length;
+    console.log(`  ${key}: ${(avg * 100).toFixed(1)}% avg (n=${vals.length})`);
+  }
+
+  console.log('\n✅ Done. View results at https://smith.langchain.com');
+}
+
+runEval().catch(console.error);
diff --git a/tests/eval/target.ts b/tests/eval/target.ts
new file mode 100644
index 000000000..8d51eafec
--- /dev/null
+++ b/tests/eval/target.ts
@@ -0,0 +1,32 @@
+import { ToolMessage } from 'langchain';
+
+import { getDefaultEnv } from '../testEnv';
+import { getAgent, getMcpServer, getModel, prompt } from './base';
+import { EvalInput, EvalOutput } from './evaluators';
+
+export async function target(inputs: EvalInput): Promise<EvalOutput> {
+  const env = getDefaultEnv();
+
+  const { agent, client } = await getAgent({
+    model: getModel(),
+    mcpServer: getMcpServer(env),
+  });
+
+  try {
+    const messages = await prompt(agent, inputs.question);
+
+    const toolsUsed = messages.reduce<EvalOutput['toolsUsed']>((acc, message) => {
+      if (ToolMessage.isInstance(message)) {
+        acc.push({
+          name: message.name ?? 'unknown tool',
+          content: message.content.toString(),
+        });
+      }
+      return acc;
+    }, []);
+
+    return { toolsUsed };
+  } finally {
+    await client?.close();
+  }
+}
diff --git a/vitest.config.eval.ts b/vitest.config.eval.ts
deleted file mode 100644
index 721c87513..000000000
--- a/vitest.config.eval.ts
+++ /dev/null
@@ -1,15 +0,0 @@
-import { defineConfig, mergeConfig } from 'vitest/config';
-
-import { configShared } from './configShared';
-
-export default mergeConfig(
-  defineConfig(configShared),
-  defineConfig({
-    test: {
-      dir: 'tests/eval',
-      testTimeout: 60 * 1000,
-      fileParallelism: false,
-      outputFile: 'junit/eval.xml',
-    },
-  }),
-);