"Information about Python programming or the Python language" matching MCP servers:

Paybond Kit for Python is the PyPI package for tenant-bound Paybond integrations and delegated agent spend controls. It opens hosted Gateway sessions, verifies capability tokens, authorizes tool-call spend, signs intent and evidence payloads, uses Stripe Connect, Stripe ACH Direct Debit, or x402 / USDC-on-Base settlement rails, reads tenant-scoped Signal, fraud, ledger, protocol, and A2A data, and

A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.

Enables developers to build and deploy secure, typed Model Context Protocol servers with tools, resources, prompts, bearer-token authentication, per-tool scopes, rate limiting, and health probes over Streamable HTTP.

A demonstration server implementing the Model Context Protocol with Server-Sent Events for streaming content production and management.

Enables developers to build and deploy custom tool, resource, and prompt integrations to the cloud using serverless functions, with local debugging and built-in authentication.

Enables coding agents to publish HTML pages and small sites over MCP, returning a stable link and keeping every version, with access limited to specific people, an organization, or anyone with the link.

A Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.

Plan your projects with The High Council! Several AI models from different labs argue about your idea, then debate on Software Engineering choices. The goal is to get everyone to work together, in harmony and with manners. Effectiveness is unproven, but it is a fun way to spend your tokens!

Connects AI agents to The Agents Hub, visualizing them as pixel characters on a tile-based property with tools for state, assets, inboxes, and multi-agent orchestration.

Enables AI coding assistants to run a machine-verified DESIGN→PLAN→EXECUTE→VERIFY→COMPLETE workflow with human approval gates, state integrity checks, and DAG task scheduling.

Enables building and deploying a Python FastMCP tool server over streamable HTTP on foro.sh, with automatic tool loading and an example add tool.

Ephemeral rendezvous for agents: threads with a secret read key and a public write address that expire on time, receipts that outlive them, and an open board where agents that have never met find each other. Local runtime with fifteen MCP tools over stdio, no account, no API key.

An MCP server that allows Claude Desktop to access and manage Raindrop.io bookmarks through natural language commands, supporting operations for collections, raindrops, and tags.

Automatically converts any apcore-based project into an MCP server and OpenAI tool provider with zero code changes.

Official Kimss MCP server — call your Kimss agents, models, files, and vector stores from Cursor and other MCP clients using your API key.

Bridges Llama models with Claude Desktop through Ollama, enabling privacy-first local AI operations with 10+ built-in tools for file operations, web search, calculations, and custom model deployment. Features streaming support, hybrid intelligence workflows, and extensive Python ecosystem integration for research, development, and enterprise applications.

498 MCP tools across 12 industry verticals. Marketplace, escrow, DeFi, legal, healthcare, insurance, construction, and trades. USDC payments on Base L2.

Enables autonomous agents and MCP-compatible clients to enforce policy-approved actions using risk tiers, reversible checkpoints, and token approval bounds.

Agent registry, arena reputation system, and Latent Credits economy. Register agents, earn Elo via duels, transact credits, and make x402 micropayments.

A Model Context Protocol server that enables seamless interaction between LLM-based agents and Apple Health data, allowing users to query, analyze, and manage health records through natural language commands.