NLWeb MCP Server

Before writing code

Fetch live spec:

1. Fetch https://github.com/nlweb-ai/NLWeb/blob/main/docs/nlweb-rest-api.md (covers /mcp route alongside /ask).
2. Read AskAgent/python/webserver/mcp_wrapper.py in the live repo for the exact JSON-RPC method list and tool schemas — these change between releases.
3. Fetch https://github.com/nlweb-ai/NLWeb/blob/main/docs/nlweb-chatgpt-integration.md for the ChatGPT-specific wiring.
4. Cross-reference with the MCP specification at https://modelcontextprotocol.io for transport rules.
5. Web-search the latest release notes for any MCP-related changes — the wrapper file's own docstring warns "Backwards compatibility is not guaranteed."

Conceptual Architecture

How NLWeb Implements MCP

NLWeb is already an MCP server out of the box — same code, second binding. The /mcp route in webserver/routes/mcp.py accepts JSON-RPC 2.0 requests and re-uses the same NLWebHandler pipeline as /ask. No separate process, no extra config.

Routes

MCP Protocol Version

NLWeb identifies itself with MCP protocol version 2024-11-05 and server name nlweb-mcp-server. Pin to this protocol version in clients until you verify a newer one is supported.

JSON-RPC Methods Supported

(prompts/list and prompts/get appear in some docs but are not in mcp_wrapper.py at the time of writing — verify.)

Tools Exposed

Three tools are advertised via tools/list:

1. ask — the primary NL query

{
  "name": "ask",
  "description": "Ask a natural-language question grounded in the site's Schema.org content.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "query": { "type": "string" },
      "site": { "type": "array", "items": { "type": "string" } },
      "generate_mode": { "type": "string", "enum": ["list", "summarize", "generate"] }
    },
    "required": ["query"]
  }
}

Note that the MCP ask tool takes site as an array (where the REST /ask takes a single string). Map accordingly in clients.

2. list_sites — enumeration

{ "name": "list_sites", "description": "List all sites the agent can query.", "inputSchema": { "type": "object", "properties": {} } }

3. who — federated discovery (conditional)

Only present when who_endpoint_enabled: true in config_nlweb.yaml. Takes {query}, returns the best NLWeb site(s) for that query — used for federated search across sites.

Streaming inside MCP

JSON-RPC 2.0 itself is request/response — no streaming. NLWeb's /mcp is NOT SSE by default. SSE only activates when the inner ask tool is called with streaming: true in its args. Most MCP clients don't expect that, so for cross-agent compatibility leave streaming off in MCP and turn it on only for clients you control.

Error Format

JSON-RPC 2.0 errors:

{
  "jsonrpc": "2.0",
  "id": 1,
  "error": {
    "code": -32603,
    "message": "Internal error",
    "data": { "errors": [...] }
  }
}

Common codes: -32700 parse error, -32600 invalid request, -32601 method not found, -32602 invalid params, -32603 internal error.

Two Parallel MCP Wrappers

NLWeb actually ships two MCP integrations:

There's also an A2A wrapper (webserver/a2a_wrapper.py, route a2a.py) for Google's Agent-to-Agent protocol, and an AppSDK adapter on port 8100 (appsdk_adapter_server.py) that translates NLWeb's message list to OpenAI Apps SDK envelopes for existing clients.

Implementation Guidance

Server-Side: Just use the built-in /mcp

You don't typically write an MCP server for NLWeb — it's already there. What you might do:

1. Verify tools/list matches your needs by hitting it from your agent client.
2. Customize the tool description if your site needs a more specific prompt — patch mcp_wrapper.py::handle_tools_list carefully (you'll re-merge on upgrade).
3. Add authentication via middleware (webserver/middleware/) — MCP has no built-in auth; bring your own (bearer token, OAuth proxy, etc.).
4. Disable who for offline / single-site deployments by setting who_endpoint_enabled: false.

Client-Side: Connecting an agent to NLWeb

# Sketch — verify against latest MCP client SDK
import httpx, json

async def mcp_call(url, method, params=None):
    payload = {"jsonrpc": "2.0", "id": 1, "method": method, "params": params or {}}
    async with httpx.AsyncClient() as c:
        r = await c.post(url, json=payload, timeout=60)
        return r.json()

# Handshake
await mcp_call("http://localhost:8000/mcp", "initialize", {"protocolVersion": "2024-11-05"})

# Discover tools
tools = await mcp_call("http://localhost:8000/mcp", "tools/list")

# Ask
result = await mcp_call("http://localhost:8000/mcp", "tools/call", {
    "name": "ask",
    "arguments": {"query": "what's new this week?", "site": ["news"], "generate_mode": "summarize"}
})

Wiring to Claude Code

Add an entry in ~/.claude.json mcpServers:

{
  "mcpServers": {
    "my-nlweb-site": {
      "url": "http://localhost:8000/mcp",
      "transport": "http"
    }
  }
}

(Verify the exact Claude Code MCP config schema in current docs — it changes.)

Wiring to ChatGPT

ChatGPT Apps SDK requires the separate Node.js MCP server in openai-apps-sdk-integration/nlweb_server_node/. It bundles a React widget that renders the nlweb-list tool's results. Follow docs/nlweb-chatgpt-integration.md for the exact registration steps — ChatGPT's MCP app store rules change.

Wiring to Gemini

Gemini's tool-calling supports MCP via the Vertex AI Agent SDK. Point it at http://your-nlweb-host:8000/mcp and call tools/list → tools/call.

Gotchas

• The MCP wrapper's docstring explicitly warns that backwards compatibility is not guaranteed. Pin your client to the same NLWeb release you tested against, and re-verify tools/list on every upgrade.
• The site arg differs between /ask (string) and /mcp::ask (array). Don't confuse them.
• /mcp is not SSE by default. Don't wire your client expecting EventSource.
• The AppSDK adapter (port 8100) is its own thing — only ChatGPT Apps SDK clients should hit it; native MCP clients use port 8000's /mcp.

Always re-fetch mcp_wrapper.py and the chatgpt-integration doc before generating final code.