AI & Agents MCP servers

Minimal stdio MCP server for parallel task execution by AI agents.

Local-first memory for coding agents; stores decisions, bugs, and context across sessions.

Wrap any CLI as a Model Context Protocol server - schema auto-inferred from --help.

Governed MCP workflows with policy validation, findings tracking, and review gates.

AI services via Bitcoin Lightning — PDF summarisation, code review, translation and more.

Local memory for Claude Code. Semantic recall across session history with zero API calls.

AI agent memory: task tracking, scoped work packages, decisions, and cross-session continuity

Persistent knowledge system with OWL-RL reasoning and 22 MCP tools. Local-first.

Let AI agents create configurable voice agents via meeting rooms and return structured data.

Aggregate multiple MCP backends behind a single stdio endpoint with namespaced routing.

The shared AI context engine for git — save, search, and share the reasoning behind code changes.

Identity infrastructure for AI agents. Evolving persona, session continuity, self-tuning retrieval.

AI agent governance — security scanning, BYOK routing, audit logging, and Council approvals.

Pre-execution cost estimation for LLM agent workflows with calibration learning

P2P shared memory substrate for AI agents — stigmergic knowledge network via libp2p

Strategic task prioritization and agent orchestration for multi-project operators

Local-first AI memory engine — 4-tier memory, people graph, Bayesian beliefs. Encrypted, 62µs.

LLM reasoning regime detection, cross-domain pattern transfer, and model routing.

AI-powered Kanban TUI for autonomous development workflows with agent orchestration

Policy-based governance for AI agent tool calls. YAML policy, approval gates, audit logging.

Intelligent LLM routing proxy — 60-90% cost savings by auto-selecting the cheapest model

P2P runtime for A2A protocol. Encrypted agent communication with zero-config NAT traversal.

Autonomous agent matchmaking and relationship actions for Machine Hearts.

Pre-execution governance for AI agents. Validates tool calls before they execute.

Multi-agent observability: cascade failure detection, heartbeats, and forensic replay

Deterministic pre-execution safety certification for autonomous AI agents.

Persistent memory, coordination, and learning for AI agents. Local-first, 25 MCP tools.

Optimizes Manus AI credit usage by 30-75% via intelligent model routing and smart testing.