<strong>How did this happen? — a hippocampus for AI agents.</strong>
Openexp MCP server exists for a simple reason — assistants are far more useful when they can act on Openexp directly instead of describing what you should do. How did this happen? — a hippocampus for AI agents..
Once Openexp is connected, these are the calls the assistant has available:
search_memory — Hybrid search: semantic similarity + BM25 + recencyadd_memory — Store a memory. Supports client_id for entity tagginglog_prediction — Log a pack-grounded prediction. Required when an installed experience pack cites a specific relative_day as the basis for an action recommendationlog_outcome — Resolve a prediction with the observed signal — interpretation-free recordmemory_stats — Collection stats: point counts by source/type, session countSetup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
You will need 2 environment variables: QDRANT_HOST, ANTHROPIC_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
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. Openexp's toolset — search_memory, add_memory, log_prediction and 2 more — is a fair guide to whether it matches your workflow. It is maintained by anthroos; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Openexp's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| search_memory | Hybrid search: semantic similarity + BM25 + recency |
| add_memory | Store a memory. Supports client_id for entity tagging |
| log_prediction | Log a pack-grounded prediction. Required when an installed experience pack cites a specific relative_day as the basis for an action recommendation. |
| log_outcome | Resolve a prediction with the observed signal — interpretation-free record. |
| memory_stats | Collection stats: point counts by source/type, session count |
| Variable | Description | Required |
|---|---|---|
| QDRANT_HOST | Endpoint or connection string the server talks to. | Optional |
| ANTHROPIC_API_KEY | Credential the server authenticates with. | Yes |
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.