Ori implements human cognition as mathematical models on a knowledge graph. Activation decay from ACT-R. Spreading activation along wiki-link edges. Hebbian co-occurrence from retrieval patterns.…
Ori Mnemos is an MCP project maintained in the aayoawoyemi/ori-mnemos repository. The maintainer describes its purpose as “Ori implements human cognition as mathematical models on a knowledge graph. Activation decay from ACT-R. Spreading activation along wiki-link edges. Hebbian co-occurrence from retrieval patterns…”. Read the project documentation for the complete scope.
The project provides a local client configuration using ori. Follow the repository’s build and installation steps before copying it, and replace example paths with the paths on your own computer.
The example declares ORI_VAULT. Secret-looking values have been replaced with placeholders. Required and optional labels are shown only when the documentation states them.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| ori_wake | Session boot: bounded briefing, plus onboarding on a fresh vault |
| ori_update | Write to identity, goals, methodology, daily, or reminders |
| ori_update_decision | Record the user's answer to an update notice |
| ori_whats_new | Release notes for the installed version, or any version |
| memory_sql | Read-only SQL over the index — anything the ranking tools cannot express |
| ori_health | Full diagnostics |
| ori_add | Capture to inbox |
| ori_promote | Promote with classification, linking, and area assignment |
| ori_validate | Schema validation |
| ori_query_ranked | Full retrieval with Q-value reranking, co-occurrence PPR, and stage meta-learning |
| ori_query_similar | Semantic search (vector only, faster) |
| ori_warmth | Inspect the associative warmth field |
| ori_explore | Recursive graph traversal — PPR, sub-question decomposition, convergence detection |
| ori_prune | Activation topology analysis and archive candidates |
| ori_index_build | Build/update embedding index and bootstrap co-occurrence edges |
| was | now |
| ori_status | SELECT COUNT() FROM v_note |
| ori_query_important | SELECT title, pagerank FROM v_note ORDER BY pagerank DESC |
| ori_query_fading | ori_prune, which its own description already deferred to |
{
"mcpServers": {
"ori": {
"command": "ori",
"args": [
"serve",
"--mcp",
"--vault",
"/path/to/brain"
],
"env": {
"ORI_VAULT": "/path/to/brain"
}
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
| Variable | Description | Required |
|---|---|---|
| ORI_VAULT | Declared in the maintainer’s client configuration. | Check documentation |
Store entities, relations and observations in a local knowledge graph with the reference Memory MCP server.
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.
Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
Chat with your second brain — search, read and write vault notes through the Local REST API.
Enables AI assistants to securely interact with Azure DevOps through a standardized protocol.