"A tool to extract or read text and images from PDFs" matching MCP servers:

Enables users to directly edit authoritative Markdown context and tables within Codex, review the complete text before saving, and commit tracked immutable revisions with version history.

Enables small local models to persist and retrieve long-term user facts through remember and recall tools, using SQLite FTS5 keyword search for lightweight memory without external vector databases or heavy VRAM.

A local MCP server that lets LLM agents read EPUB books and PDF documents with outline-first navigation, precise node reads, and local SQLite persistence.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables read-only access to a local Zotero Desktop library, providing search, recent items, metadata, tags, collections, PDF attachments, and full-text search through a browser UI or MCP endpoint.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

Implements Anthropic's 'think' tool for Claude, providing a dedicated space for structured reasoning during complex problem-solving tasks that improves performance in reasoning chains and policy adherence.

Provides an MCP interface to the ROBOT command-line tool for OWL ontology editing, enabling operations like merging, reasoning, and conversion via natural language.

MCP server that enables persistent, hybrid, local memory for LLM agents, with vector + BM25 search, knowledge graph, and policy-driven retention, providing token-budgeted context injection for AI assistants.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

A modular, extensible MCP multi-server hub that gives LLMs sandboxed file access, Git operations, web fetching, and persistent memory, deployable via Ansible.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables ChatGPT to search and fetch approved local Markdown notes through a private, read-only connection, returning results with file names, line numbers, and source context.

Enables agents to search a document collection by query, fetch a complete document by its ID, and generate bounded summaries of supplied text, with Pydantic-validated tool inputs.

Enables AI agents to record and query reasoning steps in SQLite, offloading trace data from the context window, with DAG support and persistent cross-session memory.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.