"Connecting to a vector knowledge base" 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 an autonomous agent wallet on Base to make payments, approve tokens, swap on Uniswap V3, Aerodrome, 0x and CoW Protocol, lend/borrow via Aave V3 and Morpho Blue, trade perps on Hyperliquid, and enforce risk policies via blacklists, caps, simulation, and audit logs.

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.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

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.

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.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

This MCP server provides persistent memory integration for chat applications by utilizing a local knowledge graph to remember user information across interactions.

A Model Context Protocol server that converts Markdown content to HTML format.

Enables agents to track causal relationships, reconcile concurrent state changes, and coordinate consensus across distributed networks using vector clocks, CRDTs, gossip, and quorum-based protocols.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

Enables AI agents to get read-only trust verdicts on knowledge records by evaluating evidence maturity, provenance, intended use, risk level, and scope before deciding whether knowledge may be used.

MCP server for qualifying and responding to inbound leads in seconds using a multi-agent AI pipeline.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

An MCP server that enables AI agents to execute sandboxed JavaScript code to control external web applications in real-time. It utilizes WebSockets to synchronize script execution with frontend animations, allowing complex UI interactions to be handled in a single agent turn.

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

Enables agents to stamp events with vector clocks, resolve state via LWW CRDT reconciliation, and coordinate distributed swarms through token-bucket gossip, Raft leader/quorum voting, and two-phase commit. It runs over MCP with zero external dependencies, delivering deterministic happens-before causal ordering and convergence across agent networks.

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

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.