Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host.
Project description
neruva-mcp
Model Context Protocol server for Neruva — text-embeddable Pinecone-compatible vector memory + HD-native substrate (knowledge graphs, analogy, causal do-operator). Drop-in for any MCP host. Same 22 tools as the TypeScript package, for Python-only hosts.
Install
pip install neruva-mcp
export NERUVA_API_KEY=... # from https://app.neruva.io
Or zero-install via uvx:
uvx neruva-mcp
Use
Add to your MCP host's config. Example for Claude Code:
claude mcp add neruva -- uvx neruva-mcp -e NERUVA_API_KEY=YOUR_KEY
Or run directly:
NERUVA_API_KEY=YOUR_KEY neruva-mcp
The 4-layer mental model
- Memory = semantic recall (Pinecone-compatible drop-in)
- KG = mutable structured state (deploy state, project status, refactor tracking)
- Causal = "if I do X, what happens?" (Pearl do-operator)
- Analogy = pattern transfer in HD feature space (experimental, sub-ms)
Tools (22)
Memory
| Tool | What it does |
|---|---|
memory_embed |
Encode texts to D=1024 vectors via the server-side static-MRL encoder. No BYOE. |
memory_upsert_text |
Embed and upsert text in one call -- the all-in-one for new users |
memory_query_text |
Embed a text query and search in one call |
memory_create_index |
Create a Pinecone-compatible vector index |
memory_list_indexes |
List your indexes |
memory_describe_index |
Describe one index |
memory_stats |
Per-namespace vector counts |
memory_upsert |
Insert/update raw vectors |
memory_query |
Cosine top-K search (raw vectors) |
memory_fetch |
Fetch vectors by id |
memory_update |
In-place edit values/metadata |
memory_delete |
Delete by id |
memory_export |
Portable .nmm export |
memory_import |
.nmm import |
memory_bind_role |
Bind a role atom for compound queries |
memory_read_roles |
Recover bound role atoms |
HD-native substrate
| Tool | What it does |
|---|---|
hd_kg_add_fact |
Add (subject, relation, object) to a KG (sharded K=16) |
hd_kg_query |
Query KG for object of (subject, relation) |
hd_kg_delete_fact |
Cancel a previously-added fact (mutable state) |
hd_analogy |
Four-term analogy in HD space (n_feat up to 20) |
hd_causal_add_worlds |
Add worlds to a structural causal model |
hd_causal_query |
Observational or interventional (Pearl do-operator) |
Env
| Variable | Default |
|---|---|
NERUVA_API_KEY |
required |
NERUVA_URL |
https://api.neruva.io |
License
MIT — Clouthier Simulation Labs.
Project details
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