MCP-dump

What is MCP-dump?

MCP-dump is a monorepo hosting multiple Model Context Protocol (MCP) server and client implementations. It explores different tooling stacks (Python + uv, TypeScript + Cloudflare Workers) and agent patterns (LLM-backed analysis, reactive agents, tool invocation), intended as a playground and reference for learning, prototyping, and comparing implementation styles.

How to use MCP-dump?

To use the Cloudflare Workers MCP server, navigate to mcp-hello, install dependencies with npm install, run tests with npm test, and optionally start with npx wrangler dev. For the Python MCP workspace (mcp-files), use uv run mcp-server to start the server, or run client examples like uv run examples/clients/react_agent.py. The Postgres AI agent (ai-agent-postgres-mcp) can be started with uv run main.py after reviewing its local README for database setup. The uv tool is required for Python projects.

Key features of MCP-dump

• Monorepo with multiple MCP server and client implementations
• Cloudflare Workers MCP server (TypeScript)
• Python MCP server with tooling abstractions and CLI
• AI agent example connecting MCP to Postgres
• Example clients including a reactive agent pattern
• Experimental Python minimal MCP server

Use cases of MCP-dump

• Learning the Model Context Protocol by exploring runnable examples
• Prototyping tool invocation and agent patterns
• Comparing MCP implementation styles across runtimes
• Building an AI agent that converses with a Postgres database via MCP
• Developing and testing MCP tools in a structured workspace

FAQ from MCP-dump

What is the Model Context Protocol (MCP)?

MCP standardizes how tools, agents, and large language models exchange contextual information, resources, and tool invocation results. It aims to provide predictable, typed exchanges and reduce ad‑hoc prompt engineering glue.

What runtime dependencies does MCP-dump require?

Cloudflare Workers examples require Node.js and npm (or pnpm/yarn). Python projects use uv (fast package manager) and are organized with pyproject.toml. The uv tool must be installed separately (see docs.astral.sh/uv).

How is the repository structured?

The monorepo contains subdirectories: mcp-hello (Cloudflare Workers server), mcp-files (Python workspace with a server, clients, and tools), ai-agent-postgres-mcp (AI agent for Postgres), and experimental examples. Each project has its own README.

Are these implementations production‑ready?

No. The disclaimer states these implementations are experimental, not guaranteed production‑grade, and may simplify security, robustness, and performance for clarity.

How can I contribute to MCP-dump?

Contributions are welcome, including new MCP tool modules, additional runtime adapters (Rust, Go, etc.), agent strategy examples, and documentation improvements. You should fork, branch from main, implement, add minimal docs/tests, and open a PR with a clear description.