"Retrieving information from document directory with search and memory capabilities" matching MCP servers:

Provides AI assistants with semantic search and read access to local files and directories, enabling knowledge retrieval from indexed content.

Enables MCP clients to run offline-first web search, fetch and extract web content, build a local hybrid-retrieval knowledge base, and use persistent session memory without external API keys. It also supports intent-aware federated search, semantic reranking, entity graph exploration, and source-cited deep-search answers using local models.

Enables users to convert a vendor partner directory (such as PartnerPage or the Shopify Partner Directory) or a trade body member list into one company row per listing, each carrying website, domain, tier, tags, and location for Clay-ready output. It runs the extraction on Apify, returning dataset rows for up to 20 directory URLs with optional deduping, detail enrichment, and a cost cap.

Search, inspect and compare infrastructure tools for AI agents from a checked directory.

An MCP server that exposes documents.js's document conversion, .odb, metadata, and font tooling as MCP tools, enabling agents to convert, inspect, and edit a wide range of document formats over stdio.

Deep directory tree visualization tool enabling efficient visualization of complex directory structures with AI-powered analysis capabilities.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

Enables MCP clients to browse a read-only catalog of published products and their documented interfaces, listing entries, fetching one by stable ID, and searching names, descriptions, and limitations with optional protocol filters. It also exposes the versioned manifest as a resource and a prompt that helps clients match a task to catalog entries without inventing unsupported capabilities.

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

Enables AI agents to get evidence-backed allow, review, or block decisions before installing or invoking third-party tools, with trust-aware discovery, official docs search, and prediction-market risk preflight.

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

Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.

Enables document format conversion between Word, Markdown, PDF, HTML, and plain text, supporting batch operations and format validation via the AI MCP protocol.

MCP server for managing product documentation as markdown files. Supports creating, reading, updating, deleting, and searching docs with optional semantic search.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Provides access to the APIs.guru directory of 3,000+ OpenAPI specs and supports custom spec import, enabling API discovery, analysis, and integration via natural language.

Enables AI agents to search, deep-read, and build knowledge bases from Markdown, PDF, DOCX, and PPTX documents via MCP tools for retrieval, document navigation, and ingestion.

Enables agents to discover OP-verified merchants accepting Bitcoin Lightning, BOLT12, L402, or USDT payments, with tools for search, merchant details, and payment endpoint verification.

Enables AI agents to efficiently manage and update component documentation with precise partial updates, saving up to 75% tokens compared to full rewrites.

Enables NPC agents to read, write, search, and manage a shared corporate document store, and to turn Mission Scripts into structured report outlines and scaffolds aligned to strategic intent.

An MCP server that enables users to query documents from Google Drive using AI assistance, providing tools for searching vector databases and generating answers based on document content.

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

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Checks documents against international standards (e.g., ICAO, Hague-Visby) to verify internal consistency and completeness, returning a machine-readable verdict for agent decision-making.

Enables users to search Reddit by keyword or subreddit, read thread URLs with comments, filter and sort results, and receive flat post and comment rows without needing a Reddit login or API key.

Provides access to microCMS documentation, enabling AI assistants to search and retrieve the latest document content.

Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.

MCP server for rendering, parsing, converting, and editing Office documents (Excel, PowerPoint, Word) from a structured JSON spec, using LibreOffice WASM for conversion and preview.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.

MCP server for persistent, semantic memory across AI sessions; store context, decisions, and learnings and recall them with natural language search.