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jagoff

MEMO MCP Server

by jagoff
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Local

memo_ask

Read-onlyIdempotent

Answer questions by retrieving relevant durable memories and generating a cited synthesis, using repository knowledge as additional grounding.

Instructions

Answer a question using memo retrieval and citations.

Read-only. Use when you want a synthesized answer grounded in durable memories instead of raw hit lists. k, type, and snippet_chars tune retrieval; source attributes consult logging. With client sampling enabled, synthesis runs on the calling model (see synthesizer field).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoNumber of memories to retrieve as grounding (top-k).
typeNoRestrict retrieval to one memory type (e.g. 'decision', 'fact'); None searches every type.
sourceNoCalling layer for consult attribution (e.g. 'claude-code', 'codex'); empty falls back to client info.
questionYesNatural-language question to answer from durable memories.
session_idNoTracked memo session id to associate the answer with.
include_reposNoAlso search indexed repository knowledge, not just memories.
snippet_charsNoCharacter cap per cited snippet; None uses the default.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed7 schema fields changedv4.4.6
    • addedInput schema / properties / include_repos / description
      Added value: +"Also search indexed repository knowledge, not just memories."
    • addedInput schema / properties / k / description
      Added value: +"Number of memories to retrieve as grounding (top-k)."
    • addedInput schema / properties / question / description
      Added value: +"Natural-language question to answer from durable memories."
    • addedInput schema / properties / session_id / description
      Added value: +"Tracked memo session id to associate the answer with."
    • addedInput schema / properties / snippet_chars / description
      Added value: +"Character cap per cited snippet; None uses the default."
    • addedInput schema / properties / source / description
      Added value: +"Calling layer for consult attribution (e.g. 'claude-code', 'codex'); empty falls back to client info."
    • addedInput schema / properties / type / description
      Added value: +"Restrict retrieval to one memory type (e.g. 'decision', 'fact'); None searches every type."
  2. Changed3 schema fields changedv4.4.4
    • addedInput schema / properties / snippet_chars / anyOf
      Added value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]
    • changedInput schema / properties / snippet_chars / default
      Previous value: -800New value: +null
    • removedInput schema / properties / snippet_chars / type
      Removed value: -"integer"
  3. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true. Description adds context about client sampling and synthesizer field, and reinforces read-only nature. No contradictions.

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?

Four sentences, front-loaded with purpose, followed by usage guidance and parameter roles. No fluff, every sentence adds value.

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?

Given 7 parameters and presence of output schema, description covers core functionality, usage context, read-only nature, parameter tuning, and client sampling. Missing specifics on return format, but output schema exists to fill that gap.

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

Parameters3/5

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

Schema coverage is 100%, baseline is 3. Description adds context for some parameters (k, type, snippet_chars, source) but does not explain all (e.g., session_id, include_repos). Schema descriptions are already comprehensive.

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

Purpose5/5

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

Clearly states the tool answers a question using memo retrieval and citations. Distinct from sibling tools like memo_search which return raw hit lists.

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

Usage Guidelines4/5

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

Explicitly states when to use 'synthesized answer grounded in durable memories instead of raw hit lists'. Mentions parameter tuning but does not explicitly list when not to use or alternatives.

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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