Skip to main content
Glama
jagoff

MEMO MCP Server

by jagoff
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Local

memo_chat_ask

Read-onlyIdempotent

Get grounded answers to conversational questions by using prior chat history and session context to retrieve relevant memories.

Instructions

Answer a conversational question with optional history and context.

Read-only. Use instead of memo_ask when prior turns or explicit context should shape retrieval and synthesis. history is a list of chat messages; session_id links the answer to a tracked memo session. 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.
contextNoExtra structured context for synthesis (bounded to 256KB); merged with session_id when given.
historyNoPrior chat turns as {'role', 'content'} dicts; bounded (128 items / 512KB) and used to shape retrieval.
questionYesNatural-language question for this conversational turn.
session_idNoTracked memo session id linking the answer to a session.
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. Changed8 schema fields changedv4.4.6
    • addedInput schema / properties / context / description
      Added value: +"Extra structured context for synthesis (bounded to 256KB); merged with session_id when given."
    • addedInput schema / properties / history / description
      Added value: +"Prior chat turns as {'role', 'content'} dicts; bounded (128 items / 512KB) and used to shape retrieval."
    • 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 for this conversational turn."
    • addedInput schema / properties / session_id / description
      Added value: +"Tracked memo session id linking the answer to a session."
    • 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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description reinforces this with 'Read-only' and adds context about synthesis running on the calling model with client sampling, which is beyond annotations.

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?

The description is very concise: four sentences, front-loaded with the core purpose, and no unnecessary words. 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?

With 8 parameters (1 required) and an output schema, the description covers the main purpose and key distinctions. It doesn't detail every parameter, but the schema does, and the description adds the conversational context and guidance vs memo_ask.

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%, so baseline is 3. The description adds meaning by explaining that history is a list of chat messages, session_id links the answer to a tracked session, and context is used for synthesis. This enriches the schema descriptions.

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?

The description clearly states the tool answers a conversational question with optional history and context. It distinguishes itself from the sibling memo_ask by specifying when to use this tool instead, mentioning prior turns or explicit context shaping retrieval.

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?

The description provides explicit guidance on when to use this tool over memo_ask: when prior turns or explicit context should shape retrieval. It also hints at client sampling and synthesizer field but doesn't give exhaustive usage scenarios.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jagoff/memo'

If you have feedback or need assistance with the MCP directory API, please join our Discord server