claude-memory
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | OpenAI API key for embeddings | |
| ANTHROPIC_API_KEY | Yes | Anthropic API key for synthesis | |
| MEMORY_USER_CONTEXT | Yes | User context string, e.g., 'Jane Doe, founder of Acme' |
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_memoryA | Search the memory system by semantic similarity. Use this at the start of any topic-specific conversation to surface relevant context, prior decisions, and evolved thinking — without being asked. Returns memories ranked by relevance × salience. |
| save_memoryA | Save a new memory. Use this to record decisions made, insights surfaced, how the user's thinking has evolved, feedback given, or important context from this conversation. |
| get_context_briefA | Get a synthesized brief on a topic — what is known, how thinking has evolved, and what open questions remain. Use before deep-diving into any recurring topic like web onboarding tests, the stock portfolio, or an M&A situation. |
| get_relatedC | Given a memory ID, find semantically related memories. Implements spreading activation. |
| consolidateA | Run the consolidation job: extract semantic patterns from recent episodic memories. Run this at the end of sessions covering important topics. This is what makes the memory system get smarter over time. |
| list_memoriesC | List recent memories, optionally filtered by type. |
| memory_statsA | Return total memory count and breakdown by type. |
| log_assessmentA | Log a forward-looking assessment to the judgment ledger. Use this whenever making a prediction, recommendation, or forward-looking call. Prefer a numeric 'probability' (0-1) — it enables real calibration (Brier score) over time. Assessments are tracked and later scored against what actually happened. |
| list_pending_assessmentsA | List unresolved assessments from the judgment ledger. Use during weekly review to surface what needs scoring, or at session start to remind of open calls in a domain. |
| resolve_assessmentA | Mark an assessment as resolved with its actual outcome and score. score: 1 = right, 0 = partially right, -1 = wrong. Call this as soon as the outcome of a prediction is known. |
| generate_calibrationA | Extract calibration patterns from resolved assessments in a domain and write a high-salience feedback memory. Run this after a batch of resolutions in a domain. Requires at least 3 resolved assessments in the domain. |
| get_bias_mapA | Generate a structured bias report across all resolved assessments. Shows where judgment is well-calibrated vs. systematically off. Use for quarterly self-calibration review. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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