Mindset AI Sample MCP Server
Provides tools for searching Wikipedia, retrieving article details, and getting summaries of Wikipedia pages via the MediaWiki API.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Mindset AI Sample MCP ServerWhat's the weather in London?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Mindset AI — Sample MCP Server & Onboarding
A small, runnable example of an MCP (Model Context Protocol) server that connects to a Mindset AI agent. It calls only free public APIs (no keys, no customer data), so you can run it end-to-end immediately and use it as a reference for building your own.
New here? Read
START_HERE.mdfirst. It gives the global view of how a Mindset MCP server, agent, and widget fit together, then points you at the right files in order. It's written so a customer's AI coding agent can orient itself end-to-end.In one sentence: this repo has 3 small tool servers (weather, profile, wikipedia) and one translator —
mcp-http-server.js(npm run start:mcp) — that re-serves all 5 of their tools at a single/mcpendpoint in the language Mindset speaks (JSON-RPC + bearer auth +x-user-idheaders). You give AMS that one URL; the stdio (start:weather) and legacy REST (start:http) runners are not Mindset-compatible.
The 3 sample servers (5 tools)
Server | Tools | Public API | Teaches |
weather |
| Open-Meteo | the simplest possible tool (one param) + the widget example |
profile |
| none (synthetic) | identity & security — reads |
wikipedia |
| MediaWiki | a multi-tool search → detail flow |
All three are exposed together, in a Mindset-compatible way, by the translator (npm run start:mcp). See START_HERE.md → "How this repo is wired".
Related MCP server: MCP Server Basic Example
Onboarding docs (in docs/)
Doc | Covers |
Run the server locally + smoke test | |
How the agent and server authenticate — bearer vs | |
Ship to Cloud Run (public HTTPS URL for AMS) | |
Register the server, create the agent, attach the widget | |
The | |
Embed the agent in a page (SDK v3) + provision sessions (REST) |
The transport contract the Mindset agent speaks is in MINDSET_AI_COMPLIANCE.md. Canonical platform reference: https://docs.mindset.ai.
Quick start
npm install
# Start the Mindset-compatible server (the translator). Prints an API key on first run.
export MCP_API_KEY="$(node -e "console.log(require('crypto').randomBytes(32).toString('hex'))")"
npm run start:mcp # → http://localhost:8080/mcpSmoke-test it:
# List tools (no user headers needed)
curl -s -X POST http://localhost:8080/mcp \
-H "Authorization: Bearer $MCP_API_KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'
# Call a tool (tool execution requires the identity headers)
curl -s -X POST http://localhost:8080/mcp \
-H "Authorization: Bearer $MCP_API_KEY" -H "Content-Type: application/json" \
-H "x-user-id: test-user" -H "x-app-uid: test-app" \
-d '{"jsonrpc":"2.0","id":2,"method":"tools/call","params":{"name":"get_weather","arguments":{"location":"London"}}}'Full walkthrough: docs/SETUP.md.
Testing
node test-mcp-compliance.js "$MCP_API_KEY" # 10-point Mindset compliance suite
npx @modelcontextprotocol/inspector http://localhost:8080/mcp # interactive MCP InspectorThere is also an interactive browser tester at public/test.html.
Other entry points (NOT Mindset-compatible)
These exist for local experimentation only — do not register them in AMS:
npm run start:weather/start:wikipedia— single server over stdio (for Claude Desktop / MCP Inspector)npm run start:http— legacy plain-REST APInpm run start:multi-mcp— the alternate TypeScript build undersrc/(per-server/mcp/<name>endpoints)
For Mindset, always use npm run start:mcp.
License
See LICENSE.
This server cannot be deployed
Maintenance
Related MCP Connectors
MCP server for progressive tool usage at any scale (see https://klavis.ai)
POC MCP server. Tool say_hello returns 'Welcome' (agent -> MCP -> API path).
Nifty's MCP server — exposes tasks, projects, messages, and files as tools for AI agents.
- UnifAPIOAuthcom.unifapi
Hosted MCP server for live public-data APIs and Skills for AI agents.
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- AlicenseAqualityCmaintenanceAn MCP server that exposes geocoding, current weather, and multi-day forecast as typed, structured tools for AI agents via the Open-Meteo API.3MIT