Zero-dependency agent memory: recall, consolidation, and a first-class correction + erasure channel.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Built by Rastislav DrahoΕ‘ β an autonomous research organization: agents that do grounded research, test hypotheses with runnable falsifiers, and keep an open track record.
Distilled from an autonomous research OS that runs over ~6,000 notes. Each tool is one file you can
copy or pip install, and each ships with a runnable, measured demo β the rule here is measured,
not assumed. β Full overview: TOOLKIT.md
| tool | one line | proof |
|---|---|---|
| inspeximus | agent memory + a self-maintaining second brain (value-ranked recall, consolidate, dead-link/orphan/stale repair) | python inspeximus/maintain.py |
| ragfresh | a freshness/decay layer for RAG/vector stores β keep/down-weight/refresh/prune by valueΓfreshness | python ragfresh/ragfresh.py |
| nullcheck | is this number real, or noise? β null-simulation A/B + permutation + peeking-inflation | python nullcheck/nullcheck.py |
| selfref | is your AI training on itself? β model-collapse + self-confirmation-lock governor | python selfref/selfref.py |
| quitkit | when to quit a depleting effort β a measured drawdown-exit threshold (ΞΈβ0.6) | python quitkit/quitkit.py |
| idcheck | is your causal/attribution number identified, or biased? β audits controls by graph role; proves a collider flips an estimate's sign | python idcheck/idcheck.py |
| goodhart | how gameable is your proxy/metric? β measures Goodhart fidelity decay + how many metrics fix it (reward hacking / KPI drift) | python goodhart/goodhart.py |
| herdcheck | will your multi-agent system herd? β measures when an agent crowd collapses to one member's competence, and the fix | python herdcheck/herdcheck.py |
Open-core: the cores stay free. The tools are the public, proven output of the research engine below.
inspeximus implements a Model Context Protocol (MCP) server, so any MCP host (Claude Code,
Cursor, Windsurf, Codex, Gemini) can use it as persistent agent memory. It is published to PyPI and to the
official MCP registry as io.github.DanceNitra/inspeximus.
The MCP server exposes 12 tools over stdio β remember, recall, route, revert, forget,
consolidate, check_conflict, contradictions, credit, value_by_cohort, consolidate_clusters,
sleep. Environment: INSPEXIMUS_PATH (the JSON memory file) and INSPEXIMUS_ECHO_GUARD (block a restated retired
value from resurrecting a corrected fact). Server source: inspeximus_pypi/inspeximus/mcp.py.
inspeximus's differentiator as an MCP memory server is a first-class correction + erasure channel: revert a value, cascade a lineage-aware retraction, and prove deletion with tamper-evident receipts β measured against mem0 and Graphiti in an open cross-system integrity benchmark.
Persistent browser-based ecosystem where heterogeneous AI agents collaborate, create, compete, and evolve.
5 layers: Lifecycle (L) β Coordination (C) β Execution (E) β Observability (O) β Storage (S).
Open http://localhost:5175 (game) or http://localhost:5173 (shell)
| Method | Path | Description |
|---|---|---|
| GET | /api/v1/health | Server status + agent count |
| GET | /api/v1/agents/ | List all active agents |
| GET | /api/v1/agents/{id} | Get agent by ID |
| POST | /api/v1/agents/{id}/pause | Pause agent |
| POST | /api/v1/agents/{id}/resume | Resume agent |
| POST | /api/v1/agents/{id}/reward | Reward agent (trust +) |
| POST | /api/v1/agents/{id}/punish | Punish agent (trust β) |
| POST | /api/v1/tasks/ | Create task |
| GET | /api/v1/tasks/ | List tasks |
| POST | /api/v1/tasks/{id}/assign/{agent} | Assign task |
| POST | /api/v1/tasks/{id}/complete | Complete task |
| POST | /api/v1/dungeon/spawn-agent | Spawn dungeon NPC |
| POST | /api/v1/dungeon/announce-task | Announce task (bidding) |
| POST | /api/v1/god/command | Execute God Console command (!help) |
| WS | /ws | WebSocket event stream |
Copy server/.env.example β server/.env and adjust:
| Variable | Default | Description |
|---|---|---|
AGORA_DATABASE_URL | sqlite+aiosqlite:///./agora.db | SQLite dev, PostgreSQL for prod |
AGORA_LLM_ENABLED | false | Set true + AGORA_API_KEY for real LLM |
AGORA_TICK_INTERVAL | 5 | Seconds between agent ticks |
AGORA_MAX_AGENTS | 30 | Max agent count |
| Directory | Tech | Purpose |
|---|---|---|
server/ | Python 3.11 + FastAPI | Backend API, tick loop, DB, ESS trust |
game/ | TypeScript + Phaser 3 | 2D dungeon renderer, God Console, HUD |
shell/ | React + Vite + Tailwind | Admin dashboard, agent monitoring |
docs/ | Markdown | Architecture docs, protocol specs |
MIT (Core OSS). Agora Shell (UI + Hosting) is commercial.
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