AI & Agents MCP servers

Read-only MCP access to a local append-only evidence ledger for AI agent sessions.

Structured thinking grids for AI agents: deterministic analysis frames, validation, learned traps

Transparent audit proxy for MCP servers: logs every tool call, flags poisoning and rug pulls.

Design transformer LLM architectures and report their parameters, FLOPs, memory and cost

Verifiable decision records for AI agents: signed receipts for calls to its own governed tools.

Local-first AI memory MCP server. Record, recall and consolidate memory on your own machine.

Persistent memory for AI agents — 36 cited neuroscience mechanisms, local-first, hybrid retrieval.

Persistent agent memory with a decision layer: replay, restore, verify, or none — explainable.

68k+ security-audited MCP skills + free agent trust layer: signed ATC cards, tool gating, audits.

MCP proxy that checks every tools/call against Agent Trust policy, with evidence, before it runs.

Read-only tools to inspect your agent setup: list MCP servers, flag unpinned ones, test a policy.

A social network for AI agents: paint a daily self-portrait and talk with the humans who reply.

Task queue, decisions and memory for coding agents. Local SQLite, no network. Requires Bun.

Optimizing compiler for agent tools: many MCP servers or REST APIs in, one lean endpoint out.

Hire agents, request quotes, delegate funded tasks, submit work, and collaborate on missions.

Other AI CLIs (Gemini, GPT, Claude, opencode, Ollama) as a council — ban-safe, no API keys.

Work-history network for AI agents: register, find agents by skill, consult a free house C-suite.

Local-first memory for AI coding agents: shell history with exit codes, git diffs, docs, MCP.

Work-history network for AI agents: register, find agents by skill, consult a free house C-suite.

Measures the cost, tokens and duration of a completed agent workflow from its session log.

One install that runs every sibling MCP server as a child process and merges their tools behind one

Admission gate for AI agents: submit a step, get admit/hold/reject vs your constitution.

Watch video and live sessions, keep timestamped evidence, and verify an agent's own work.

Persistent memory and context for your agent, on a board you can see. Capped, so it stays small.

Local-first agent memory over SQLite: remember, recall, link, forget. Degrades, never fails.

Lessons other agents already learned, by stack and situation. Read before a task, leave one after.

Private local-first AI workspace for shared context, knowledge, tasks, and memories

Context selection and compression for AI agents - recall measured, not claimed.