"Using llama.cpp and Searxng with local models" matching MCP servers:

Enables searching, comparing, and inspecting AI models by pricing, context window, and capabilities via the models.dev catalog.

Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

MCP server that lists available GitHub Models and compares responses from multiple models for the same prompt.

An MCP server that helps interact with and compare different GitHub Models, enabling listing, filtering, and comparing model responses.

A wrapper for mcp-remote that provides secure authentication for protected MCP servers using Adobe IMS or Okta OAuth flows. It features automated token management, validation, and background refreshing for seamless access to remote resources.

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

A local development MCP server that exposes MySQL databases to VSCode and Copilot CLI with read-only SELECT queries and INSERT/UPDATE operations. It provides secure, schema-specific database access for development environments only.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables local file reading and writing for your project via Claude Desktop, with tools to read, write, and list files in a specified root path.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

Local-first memory daemon for AI coding agents that captures session transcripts, distills typed memories (decisions, facts, lessons, commands, todos), and serves them via hybrid search through MCP tools.

Enables AI coding agents to route tasks to local GPU models via a dynamic heuristic classifier, tracking real-time token dollar savings.

Provides comprehensive AI model metadata through MCP, enabling search and filtering of 100+ AI models by capabilities, pricing, context length, and provider specifications.

Enables running MCP tools against local MLX models on your Mac, with hardware-aware configuration, CLI streaming, and a dashboard for routing and monitoring.

Enables AI assistants to intelligently search and explore local file systems using native Unix commands (ripgrep, find, ls) with token-optimized output, automatic pagination, and multi-layer security validation.

Provides Claude Code with local semantic search and indexing of your codebase using AST-aware chunking and hybrid search, enabling deep code understanding without sending data to the cloud.

A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.

Enables AI agents to access user and message data through MCP resources, providing REST API integration for user management with paginated lists and thread tracking.