<strong>Graph-Based AI Memory System with EcphoryRAG Retrieval and Leiden Clustering</strong>
If you already use Smriti MCP, the smriti mcp mcp server is the piece that lets your assistant work with it directly. Graph-Based AI Memory System with EcphoryRAG Retrieval and Leiden Clustering.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
Core — The Core tool exposed by this serverEmbedding — The Embedding tool exposed by this serverBackup — The Backup tool exposed by this serverConsolidation — The Consolidation tool exposed by this serversmriti_store — The smriti_store tool exposed by this serversmriti_recall — The smriti_recall tool exposed by this serversmriti_manage — The smriti_manage tool exposed by this serverNeo4j — The Neo4j tool exposed by this serverFalkorDB — Schema migrations (e.g., adding cluster_id to existing databases) run automatically on startupConfiguration is passed through the environment: LLM_API_KEY, EMBEDDING_API_KEY, ACCESSING_USER, DYLD_LIBRARY_PATH, LD_LIBRARY_PATH, LLM_BASE_URL, EMBEDDING_BASE_URL, GIT_BASE_URL. 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.
xcode-select --install - Linux: sudo apt install build-essential - Windows: Use Docker (recommended) or MinGW - liblbug (LadybugDB shared library) — Runtime dependency for LadybugDB backend, downloadedSetup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client. The configuration blocks on this page cover the common clients.
This sits in the database access group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Smriti MCP's toolset — Core, Embedding, Backup and 6 more — is a fair guide to whether it matches your workflow. It is maintained by tejzpr; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Smriti MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Core | The Core tool exposed by this server. |
| Embedding | The Embedding tool exposed by this server. |
| Backup | The Backup tool exposed by this server. |
| Consolidation | The Consolidation tool exposed by this server. |
| smriti_store | The smriti_store tool exposed by this server. |
| smriti_recall | The smriti_recall tool exposed by this server. |
| smriti_manage | The smriti_manage tool exposed by this server. |
| Neo4j | The Neo4j tool exposed by this server. |
| FalkorDB | Schema migrations (e.g., adding cluster_id to existing databases) run automatically on startup. |
**Multi-user mode:**
```json
{
"mcpServers": {
"smriti": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-v", "/Users/yourname/.smriti:/home/smriti/.smriti",
"-e", "LLM_API_KEY=your-api-key",
"-e", "EMBEDDING_API_KEY=your-embedding-key",
"-e", "ACCESSING_USER=yourname",
"tejzpr/smriti-mcp"
]
}
}
}Configuration as documented by the project. Restart the client after saving.
xcode-select --install - Linux: sudo apt install build-essential - Windows: Use Docker (recommended) or MinGW - liblbug (LadybugDB shared library) — Runtime dependency for LadybugDB backend, downloaded| Variable | Description | Required |
|---|---|---|
| LLM_API_KEY | Credential the server authenticates with. | Yes |
| EMBEDDING_API_KEY | Credential the server authenticates with. | Yes |
| ACCESSING_USER | Configuration value read at startup. | Optional |
| DYLD_LIBRARY_PATH | Filesystem location the server is allowed to use. | Optional |
| LD_LIBRARY_PATH | Filesystem location the server is allowed to use. | Optional |
| LLM_BASE_URL | Endpoint or connection string the server talks to. | Yes |
| EMBEDDING_BASE_URL | Endpoint or connection string the server talks to. | Yes |
| GIT_BASE_URL | Endpoint or connection string the server talks to. | Yes |
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