"A map or mapping-related information" matching MCP servers:

Enables extracting explicitly stated contract metadata, clauses, and obligations from user-supplied contract text without storing or modifying the data.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

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.

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.

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

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.

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.

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().

A Model Context Protocol server that fetches up-to-date, version-specific documentation and code examples from libraries directly into LLM prompts, helping developers get accurate answers without outdated or hallucinated information.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

Provides read-only tools for planning, writing, and auditing lesion network mapping and connectome-based localization papers, including design classification, methods checklists, phrasebooks, limitations, and manuscript auditing.

Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.

stdio server to read markdown with images or index markdown headings from a file, folder or URL

An MCP server that checks whether a vendor API or SDK is active, deprecated, or sunset, using a curated dataset. Enables agents to verify deprecation status before upgrade/maintenance work.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

Lets AI agents search and read a folder of Markdown documentation at query time, exposing heading-level search, whole-page or section retrieval, and page listing as tools and resources over stdio or Streamable HTTP. Can run as a CLI, a hosted endpoint, or a library inside an existing Node or Next.js site.