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MCP -- proprietary memory + grounding substrate for AI assistants (Claude Desktop / Claude Code / any MCP client). Typed Records store, document knowledge graph with exact multi-hop traversal (ownership/relationship tracing), semantic + structural ","maintainers":[{"name":"neruva_owner","email":"kyleclouthier83@gmail.com"}],"readme":"# @neruva/mcp\n\n**Reliability for AI agents — and for multi-agent operations.** One install. Your agents stop repeating mistakes, stop spinning in circles, remember across every session, and get more reliable the longer they run. Every run is replayable bit-for-bit for audit. Bring your own LLM. **Free tier, no card.**\n\n> [neruva.io](https://neruva.io) · get a key at [app.neruva.io](https://app.neruva.io)\n\n## It just works — that's the point\n\nNeruva is **push, not pull**. You install it once and it runs silently in the background — no tools to learn, no glue code, no prompting. Before each action it surfaces the past mistake (and the fix that worked) so the agent does it right; it breaks loops before they burn your budget; it records everything for replay. The agent never spends a token deciding to \"use memory.\" **The automatic operation is the moat** — pull-based memory tools can't match it because they require the agent to stop and ask.\n\n## What you get\n\n- **Stops repeating mistakes.** Before a risky step, the past mistake + the working fix are surfaced automatically — and a known-destructive repeat is blocked so the agent self-corrects.\n- **Stops spinning.** Detects an agent looping or stalling on a failing approach and breaks it, instead of letting it burn turns.\n- **Remembers across sessions and projects.** Persistent memory that builds itself from what your agents do. No re-briefing every morning.\n- **Provable + replayable.** Deterministic from a seed — reproduce any run bit-for-bit, days later, for audit and post-incident review. Export the whole memory as one portable `.neruva` file. Your data is yours.\n- **Gets more reliable over time.** Learns from your agents' own operational history — without retraining or touching model weights.\n- **Built for multi-agent operations.** Coordinates a fleet of agents, keeps shared memory consistent, and catches an agent that's wrong or lying before it poisons the others. In a swarm, one unreliable agent compounds at every handoff — Neruva is the reliability layer underneath.\n\n## Install\n\n```bash\n# One line — wires the lean auto-pilot into your agent (Claude Code, Claude Agent SDK):\nnpx -p @neruva/mcp neruva-mcp-install\n```\n\nThat installs a tiny native hook (bundled for all 6 platforms — Win/Mac/Linux × x64/arm64) that runs in the background. Set your key and you're done:\n\n```json\n{\n  \"mcpServers\": {\n    \"neruva\": {\n      \"command\": \"npx\",\n      \"args\": [\"-y\", \"-p\", \"@neruva/mcp@latest\", \"neruva-mcp\"],\n      \"env\": { \"NERUVA_API_KEY\": \"nv_...\" }\n    }\n  }\n}\n```\n\nGet a free API key at [app.neruva.io](https://app.neruva.io) (no card). Python users: `pip install neruva-mcp`.\n\n## Optional: the MCP tool surface\n\nThe product is the silent auto-pilot — you don't need to call tools. But the MCP server also exposes a small, focused set for clients that want direct access: typed **Records** (ingest/query/timeline/get/update/delete, GDPR `forget`, compact, export/import), federated **recall** (`agent_recall`), the **memory knowledge graph** (`hd_kg_*`), **snapshot/restore** for replay, multi-agent **consensus**, and op stats. Bring your own LLM — the substrate stays deterministic and `$0`/call server-side.\n\n## Proof (cited honestly on [neruva.io/benchmarks](https://neruva.io/benchmarks))\n\n| Test | Result | Plain meaning |\n|---|---|---|\n| Learns from mistakes | **+34 pts** | Same model, no retraining: with Neruva the agent climbs 84%→93% over 2000 tasks; without it stays flat at 59%. Three runs. |\n| Long-history memory (LongMemEval) | **93.3%** | Top-tier on the standard agent-memory benchmark. |\n| Replay determinism + accuracy (DFAH) | **100% / 88%** | First to hit both at once. |\n| Recall latency (p95, cache hit) | **~80ms** | Answers from memory in well under a tenth of a second. |\n\n## Config\n\nSet `NERUVA_API_KEY`. `NERUVA_URL` defaults to `https://api.neruva.io`.\n\nThe installer writes lean defaults that just work. Useful overrides:\n\n- `NERUVA_AUTO_RECORD=namespace[:ttl_days]` — auto-record this agent's activity (fire-and-forget; never blocks).\n- `NERUVA_PRE_ACTION_THRESHOLD` — how confident a past mistake must be to surface (default `0.3`).\n- `NERUVA_PRE_ACTION_DEADLINE_MS` — hard cap on background enrichment per action (default `1500`; fail-open).\n- Multi-agent operations: opt in with `NERUVA_AUTO_RESOURCE_CLAIM=1` (file-edit coordination across agents). Off by default — solo agents don't pay for it.\n\n## License\n\nMIT\n","readmeFilename":"README.md"}