GodPrompt MCP server + portable Agent Skill for coding agents — TDD, debugging, verification gates, task routing, and progressive disclosure.

Harness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved preferences.

MCP server for AI image generation

Context compression for AI coding agents: compresses tool output before it enters the model, dedups repeats to 13-token refs. Claude Code, Cursor, Codex, Kiro, Zed, any MCP client. Rust, zero LLM calls.

🛡️ Security audit CLI for Model Context Protocol (MCP) servers — scan AI agent configs for tool poisoning, rug pulls, hardcoded secrets, command injection & supply-chain risks. Pure Python, SARIF + CI ready.

MCP server for 2kw.ai — EU-hosted AI platform: OpenAI-compatible LLM gateway, schema-driven document extraction, transcription, agents with a knowledge base, and cost observability. 199 tools for Claude Code, Cursor, and Windsurf.

Exposes a single ask_warriorgpt tool that lets Claude Code delegate self-contained code generation prompts to Wayne State's hosted model API, passing files to and from disk so the content never counts against the Claude plan. It validates multi-file edits before writing and logs per-session token usage, keeping design and debugging work with Claude.

Enables AI clients to drive local video editing projects through a CEP bridge, covering media ingest, sequence and timeline editing, effects, keyframes, captions, markers, audio, color, and exports across hundreds of discoverable tools. Ships context resources, guided prompts, and higher-level assembly workflows for agent-driven editing.

Enables AI agents and LLMs to persist facts, preferences, and observations in a local SQLite store and to build and traverse subject-predicate-object knowledge graphs across sessions. It provides fuzzy keyword search and graph queries so assistants retain context and recall prior project history without repeating prompts.

Enables building zero-dependency Model Context Protocol servers over the Streamable HTTP transport, exposing typed tools, resources and URI templates, prompts, background tasks, and OAuth-protected endpoints. It can be mounted into FastAPI, Starlette, Flask, Django or any ASGI/WSGI app, or run standalone on the Python standard library alone.

Enables searching, retrieving, summarizing, and comparing official central-bank time series, with resource and prompt access for generating reports and evaluating answers against memory-only responses.

Connects MCP hosts and LangChain agents to a local WAHA (WhatsApp HTTP API) instance, exposing tools for session management, chats, messages, contacts, and sending text, images, or files. It also provides an operational skill prompt covering lifecycle, chat ID formats, send guardrails, media rules, and error handling.

Rules-based context reduction, planning checks, research prompts and fixed experiences for agents.