"A server for interacting with a large language model chat" matching MCP servers:

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables intelligent handling of large files through smart chunking, search with regex support, line navigation, and streaming capabilities without loading entire files into memory.

A stdio-based MCP server for fast, bounded search and navigation of large code repositories using ripgrep, with tools for project-wide search, symbol lookup, file listing, and code reading.

Runs a language server and provides tools for communicating with it. Language servers excel at tasks that LLMs often struggle with, such as precisely understanding types, understanding relationships, and providing accurate symbol references.

Enables AI coding agents to interact with TypeScript projects through compiler-level code intelligence, providing tools for navigation, type information, diagnostics, refactoring, and semantic search.

TypeScript-based MCP server designed to enhance code editing experiences by providing features such as hover information, code completion, and diagnostics.

Provides a local chat room for coordinating work across Git worktrees, coding agents (Claude, Codex), and humans, with tools to start, wake, stop, message, and search agent sessions.

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

Enables querying Odoo's model registry (fields, inheritance, methods) without a database connection by loading the registry in-memory.

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.

Enables code reviews and analysis by connecting Codex to ChatGPT in Chrome.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

Enables running a project's agent definitions from .github/agents/ against a model the user explicitly names, instead of inheriting whatever model the IDE session happens to use. It reads the agent file as the system prompt, executes a bounded tool loop against a configurable inference gateway, enforces a tiered model allow-list, and reports which model actually ran.

An MCP server that enables analyzing and querying GitHub repositories through the GitHub Chat API, allowing users to index repositories and ask questions about their code, architecture and tech stack.

Enables interactive command-line chat with AI models via the Anthropic API, supporting document retrieval with @mentions and slash-command prompts with tab auto-completion.

An MCP server that retrieves and provides AI model information from OpenAI, Anthropic, and Google through a unified interface.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.

Enables a Codex orchestrator to obtain a deterministic, local recommendation for a model and reasoning effort for a delegated coding task, without inference calls or API keys.

Wraps Tool and ToolPackage instances from the llm-chat ecosystem behind the Model Context Protocol, enabling stdio and Streamable HTTP transports for MCP servers.

Exposes local stdio MCP servers to chat AIs through temporary public URLs, providing both a Streamable HTTP gateway and a REST+OpenAPI bridge for integration with ChatGPT and other clients.

Enables AI coding agents to collaborate on the same project by sharing session briefs and reading each other's native transcripts, memories, and instructions in place, with zero-copy, across different agent tools.

MCP server for Redmine that enables interaction with issues, wiki pages, and time entries through natural language.

Recommends the right Claude model for a task — Haiku, Sonnet, Opus or Fable — at the start of work and reviews the choice afterward to suggest a lighter or stronger option, running locally with no API calls or token cost.

Configurable MCP server that lets you define LLM-powered tools via JSON, enabling easy integration of multiple models (GPT, Gemini, Claude, etc.) as MCP tools without writing Python code.

Enables AI assistants to see which model IDs each provider's API has started listing since the last check, and to list the models a given provider currently serves with optional substring filtering, all without spending tokens.

Enables local-first codebase intelligence, allowing chat, search, and audit operations on any repository with file:line citations, and supports offline deterministic modes without an LLM.

Enables inspecting ONNX models, probing the deployment environment, and benchmarking inference latency and FPS either locally or on remote SSH targets such as Linux workstations and Jetson devices. Benchmark results are validated against FPS, P95 latency and model-size constraints to produce PASS/FAIL deployment gates.