whoami-mcp
Integrates with Google's Gemini API (via OpenAI-compatible endpoint) to enable the optional ask tool for answering questions about the profile.
Integrates with local Ollama models to enable the optional ask tool for answering questions about the profile without requiring an external API key.
Integrates with OpenAI's chat API to enable the optional ask tool, which answers free-form questions about the person's profile in their voice.
Click on "Install 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., "@whoami-mcpWhat projects have you worked on?"
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.
whoami-mcp
A Model Context Protocol server that exposes a person's structured professional profile — experience, projects, skills, education, certifications — as MCP tools. Point Claude (or any MCP client) at it and it can answer questions about that person from real data instead of guesswork.
One package, three ways to use it:
Library —
npm i whoami-mcp, build your own integration on the tools.Local (stdio) —
npx whoami-mcpfor Claude Desktop.Deployable (HTTP) — a stateless Streamable-HTTP server you can host (Docker-ready).
Tools
Tool | Returns |
| Name, role, company, location, bio, availability, preferred stack, links |
| Work history: companies, roles, dates, descriptions, achievements |
| Projects: tech stack, problem solved, your specific role, links |
| Skills by category with proficiency levels |
| Education history + professional certifications |
Related MCP server: mundigital
Chat (optional)
Set a chat provider and the server gains an extra ask tool — it answers
free-form questions in the person's voice, grounded in the profile, instead of
just returning raw data. Off by default (the data tools work without it).
It speaks the OpenAI-compatible /chat/completions API, so any provider
works — set a base URL + model (+ key if needed):
Provider |
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OpenAI |
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| |
Ollama (local, no key) |
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Groq |
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CHAT_BASE_URL=https://api.openai.com/v1 CHAT_API_KEY=sk-... CHAT_MODEL=gpt-4o-mini \
PROFILE_PATH=data/profile.json npm run start:httpEnv: CHAT_BASE_URL, CHAT_MODEL (both required to enable), CHAT_API_KEY
(optional), CHAT_TEMPERATURE (default 0.4). See .env.example.
Your profile
Every server reads one profile JSON with six top-level keys: basic, experience, projects, skills, education, certifications. See data/profile.example.json for the exact shape.
cp data/profile.example.json data/profile.json # then editPoint a server at it however suits your deploy (precedence top to bottom):
PROFILE_URL— fetch the JSON over HTTP (a GitHub gist, your hosted profile API, any endpoint)PROFILE_PATH— read this file./profile.json— default file in the working directory
Local (stdio) — Claude Desktop
{
"mcpServers": {
"whoami": {
"command": "npx",
"args": ["-y", "whoami-mcp", "whoami-stdio"],
"env": { "PROFILE_PATH": "/abs/path/to/your/profile.json" }
}
}
}From a clone instead: npm install && npm run build, then point command/args at node /abs/path/to/dist/stdio.js.
Deploy (Streamable HTTP)
A long-running, stateless HTTP server — host it anywhere that runs a container.
docker compose up --build # serves MCP at http://localhost:8080/mcpWithout Docker:
npm install && npm run build
PROFILE_PATH=data/profile.json npm run start:httpConnect an MCP client to the endpoint:
{ "mcpServers": { "whoami": { "url": "http://localhost:8080/mcp" } } }Health check: GET /health → {"status":"ok"}.
Build on the library
npm i whoami-mcpimport { registerTools, type NormalizedProfile } from "whoami-mcp";
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
const server = new McpServer({ name: "whoami", version: "1.0.0" });
registerTools(server, profile); // profile: NormalizedProfilewhoami-mcp/http also exports createHttpHandler(profile, opts) for Next.js / fetch runtimes.
Layout
src/
index.ts library entry — TOOLS, registerTools, types
http.ts createHttpHandler (fetch/Next factory) → exported as whoami-mcp/http
tools.ts the five tool definitions
types.ts NormalizedProfile + tool types
register.ts registerTools(server, profile)
loadProfile.ts read PROFILE_PATH / ./profile.json
stdio.ts bin: whoami-stdio
http-server.ts bin: whoami-http (deployable, SDK StreamableHTTP)npm install
npm run buildLicense
MIT — see LICENSE.
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