An MCP server that builds knowledge graphs through use. Concepts connect when they activate together. Unused connections decay. The more you use it
If you already use Hebbian Mind Enterprise, the hebbian mind enterprise mcp server is the piece that lets your assistant work with it directly. An MCP server that builds knowledge graphs through use. Concepts connect when they activate together. Unused connections decay. The more you use it, the smarter it gets.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
save_to_mind — Store content with automatic concept activation and edge strengtheningquery_mind — The query_mind tool exposed by this serveranalyze_content — The analyze_content tool exposed by this serverget_related_nodes — Returns the neighborhood graph - concepts that have fired together with "security"list_nodes — The list_nodes tool exposed by this servermind_status — Returns node count, edge count, memory count, strongest connections, dual-write statusfaiss_search — The faiss_search tool exposed by this serverfaiss_status — The faiss_status tool exposed by this serverConfiguration is passed through the environment: HEBBIAN_MIND_THRESHOLD, HEBBIAN_MIND_FAISS_HOST. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
The server ships on PyPI as mcp, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Hebbian Mind Enterprise's toolset — save_to_mind, query_mind, analyze_content and 5 more — is a fair guide to whether it matches your workflow. It is maintained by for-sunny; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Hebbian Mind Enterprise's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| save_to_mind | Store content with automatic concept activation and edge strengthening. |
| query_mind | The query_mind tool exposed by this server. |
| analyze_content | The analyze_content tool exposed by this server. |
| get_related_nodes | Returns the neighborhood graph - concepts that have fired together with "security". |
| list_nodes | The list_nodes tool exposed by this server. |
| mind_status | Returns node count, edge count, memory count, strongest connections, dual-write status. |
| faiss_search | The faiss_search tool exposed by this server. |
| faiss_status | The faiss_status tool exposed by this server. |
{
"mcpServers": {
"hebbian-mind": {
"command": "python",
"args": ["-m", "hebbian_mind.server"]
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| HEBBIAN_MIND_THRESHOLD | Configuration value read at startup. | Optional |
| HEBBIAN_MIND_FAISS_HOST | Endpoint or connection string the server talks to. | Optional |
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.