mcp_quote_server

MCP server implementation

Setup MCP configuration

Ensure the .mcp.json points to correct root folder of the project

Related MCP server: Test MCP Server

Part 0: Run MCP Server

uv run python quote_server/quote_mcp_server.py

Part 1: The MCP server (no API key needed)

The server is quote_server/quote_mcp_server.py: ~65 lines built on the MCP Python SDK's FastMCP helper. It reads quotes.json and exposes two tools:

1.1 — Smoke-test it (recommended)

try_server.py launches the server over STDIO, speaks MCP to it, and prints a few sample calls. No LLM, no browser, no Node — just the mcp SDK you already installed:

uv run python try_server.py

Tools: list_categories, get_quote
Categories: creativity, engineering, humor, motivation, stoicism
A stoic quote: “We suffer more often in imagination than in reality.” — Seneca
Unknown category 'banana': '' (nothing, as expected)

That's a complete, working MCP server. Everything below is just pointing different hosts at it.

1.2 — Optional: the MCP Inspector

The MCP Inspector is Anthropic's official tool for poking at servers (needs Node/npx). It has two modes.

CLI mode (recommended — no browser, scriptable):

# list the tools
npx @modelcontextprotocol/inspector --cli \
  uv run python quote_server/quote_mcp_server.py \
  --method tools/list

# call a tool
npx @modelcontextprotocol/inspector --cli \
  uv run python quote_server/quote_mcp_server.py \
  --method tools/call --tool-name get_quote --tool-arg category=stoicism

The second command prints the quote as JSON. (If your npm registry rejects scoped packages, add --registry=https://registry.npmjs.org to npx.)

GUI mode:

Point the Inspector at our .mcp.json (the same file Claude Code uses) and name the server — it opens with the STDIO transport and command pre-filled:

npx @modelcontextprotocol/inspector --config .mcp.json --server quotes

A browser tab opens with Transport Type: STDIO, Command: uv, and our arguments already populated. Click Connect (top-left) — the status flips to Connected — then open the Tools tab, List Tools, and run them.

(The committed .mcp.json has an absolute --directory path. If you cloned the repo somewhere other than ~/git/summit-ai-mcp-demo, edit that path first — or regenerate the file with the Claude Code step in 3.1.)

Part 2: Claude Code

claude mcp add quotes --scope project \
  -- uv --directory ~/Dev/Python/mcp_quote_server run python quote_server/quote_mcp_server.py

This writes a .mcp.json in the repo (already committed here as a reference). Run claude in the repo and approve the project server when prompted, then:

> give me a quote about creativity

Verify anytime with inside claude with /mcp

Part 3: Graphify the codebase

Use lower-cost model like minimax3 using Ollama in Claude code

ollama launch claude --model minimax-m3:cloud

Graphify the codebase inside ~/Dev/Python/mcp_quote_server, using skill

/graphify .

The code-base graph would be available inside folder graphify-out