"Convert a PDF into a Graph DB Representation for Decision Trees" matching MCP servers:

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.

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.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

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.

Provides deterministic decision and constraint evaluation for AI agents. Supports ruleset validation, fact evaluation, and constraint checking via MCP tools.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

An LLM-native decision tracking system that captures unexpected engineering outcomes as 'pressure events' to build a persistent learning foundation. It enables AI assistants to manage cases, log surprises, and promote recurring insights into global or project-specific knowledge bases.

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Enables LLMs to break down reasoning into an explicit, editable graph of thinking steps, with visualizations and the ability to revise individual steps.

Enables persistent, full-text-searchable context for AI agents, including session tracking, event logging, todo management, and tagged context retrieval.

Enables founders to evaluate startup ideas with evidence-calibrated reports, manage portfolios, and access evaluation history through natural language.

Provides agent certification and trust verification tools for AI agents, enabling certification checks, trust score calculations, audit ticket issuance, and emergency kill switch activation through the A-SOC trust network.

Enables AI assistants to access and execute automated decision services from IBM Decision Intelligence or IBM Automation Decision Services. It exposes deployed decision operations as tools for platforms like Claude Desktop and IBM watsonx Orchestrate.

An MCP-based trivia game server where AI creates rounds with two true statements and one false 'twist' about various topics, letting players guess which statement is false.

Enables AI agents to store, query, and trace a time-aware memory graph of nodes and edges in a single SQLite file, supporting weighted recall, temporal queries, and provenance-aware writes over MCP.

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables AI coding agents to store and query procedural knowledge as RDF triples, returning localized guidance, ranked next steps, and fastest successful paths while recording transition outcomes and task rollouts. Supports self-evolving graph maintenance through proposed mutations, held-out validation gating, negative memory of rejected proposals, and idempotent evidence imports.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

Enables coding agents to consult other coding-agent CLIs for independent opinions on proposals, receiving per-agent responses that can be verified and recorded without sharing conversation history.