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engram-mcp

engram-mcp

by Cartisien
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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recall

Retrieve relevant memories via semantic search with keyword fallback across working and long-term tiers. Optionally blend cross-session user memories.

Instructions

Retrieve relevant memories via semantic search (falls back to keyword). Searches working + long_term tiers. Pass userId to blend in cross-session user facts.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sessionId": "<sessionId>",
      "query": "<query>"
    },
    "name": "recall"
  }
}

Input Schema

NameRequiredDescriptionDefault
sessionIdYesSession identifier
queryYesSearch query
limitNoMax results (default 10)
userIdNoOptional: also blend in this user's cross-session memories
tiersNoComma-separated tiers to search: working,long_term,archived (default: working,long_term)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description provides good behavioral context: semantic search with keyword fallback, default tiers (working+long_term), and the effect of userId. It doesn't disclose side effects or rate limits, but that is acceptable for a read operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences that front-load the core action and key details. Every sentence is meaningful, with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters and no output schema, the description covers the key behavioral aspects: search type, tiers, and user blending. It omits return format, but that is reasonable without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. The description adds value by explaining the search mechanism and the purpose of userId beyond the schema. It compensates for the schema's minimal descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves memories via semantic search with keyword fallback, specifying tiers and optional user blending. It distinguishes its general-purpose nature from sibling tools like recall_by_time or recall_recent, though it doesn't explicitly name them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (general memory retrieval with semantic search) and hints at optional userId for cross-session facts, but it lacks explicit guidance on when not to use or alternatives, leaving some ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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