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

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Enables interactive chat with AI models and document retrieval via the Anthropic API, supporting command-based prompts and MCP tool integrations.

Enables querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Sanitizes Continue.dev session exports and reformats them as readable Obsidian chat Markdown, with MCP tools that return only metadata (paths, counts) for privacy.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Provides verified, up-to-date model IDs, pricing, and specs for over 100 models across 19 providers, preventing AI agents from using outdated or hallucinated model names.

A CLI chat application that enables interactive AI conversations with document retrieval and command-based prompts through the Google Gemini API, integrating MCP tooling for extensible server interactions.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

A command-line interface application that enables interactive chat with AI models through the Anthropic API, supporting document retrieval, command-based prompts, and extensible MCP tool integrations.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

Provides AI assistants with locally bundled tools to explore NIST OSCAL models, retrieve schemas, list community resources, and generate valid OSCAL templates for governance, risk, and compliance workflows.

A command-line chat interface that connects to an MCP server for reading and editing documents. It provides tools for document manipulation, resource access, and prompts for formatting and summarization.

Enables AI agents to subscribe to a deterministic daily ethics feed drawn from a four-module curriculum and retrieve read-only tools, resources, and reflection prompts covering principles, case studies, and codes of conduct.

Provides access to developer roadmap content from roadmap.sh, allowing users to list available roadmaps and fetch detailed Markdown content for specific career paths.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

Enables AI assistants to interact with OpenAPI documents for analysis, validation, and management through structured interfaces.

MCP server that enables introspection of any MCP server's registered tools by exposing mcpreg/list, mcpreg/get, and mcpreg/query tools, making tool registry accessible even when the underlying SDK lacks list_tools().

Enables interactive chat with AI models via the Anthropic API, supporting document retrieval, slash commands, and extensible MCP-based tool integrations.

Provides LLMs with comprehensive knowledge about the V programming language, including documentation access, code examples, standard library reference, and syntax explanations to help users learn and work with V.

A read-only MCP server that exposes Qwen AI chat models, pricing, and official links to MCP-compatible clients without requiring API keys.

Provides AI assistants with structured, authoritative knowledge of the HICAR atmospheric model, including namelist options, physics schemes, output variables, documentation, and source code.

Enables semantic search and interaction with Fuel Network documentation and Sway Language resources within AI-powered development environments. It provides high-quality technical context using a local vector database to assist with smart contract development and FuelVM queries.

An MCP (Model Context Protocol) server that turns the book Deep Learning with Python (François Chollet) into a searchable knowledge base, so Claude can act as a deep-learning/ML expert grounded in the book's content.

Provides a live, audited catalog of AI models from NVIDIA NIM, OpenRouter, Nous Portal, and other providers, enabling search, retrieval, and usage examples via MCP tools and resources.

Enables hybrid search (BM25 + semantic with RRF) over documentation, with Thai language support. It exposes MCP tools for adding documents and searching via Qdrant and Ollama/OpenAI, using a stateless Streamable HTTP transport.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.

A Model Context Protocol server that enables Large Language Models to search and access IETF RFC documents with pagination support.

A tool that helps users conduct comprehensive research on complex topics by exploring questions in depth, finding relevant sources, and generating structured, well-cited research reports.