midas-memory-mcp

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Remember code memory

remember_code

Capture code memories tagged by project and category (e.g., architecture decision, bug fixed) for coding agents, with provenance and importance.

Instructions

Capture a CODE memory tagged by category + project, for the coding-agent views. code_kind: one of architecture_decision | dependency_choice | convention | bug_fixed | recurring_failure | forbidden_action | command_worked | command_failed. Use forbidden_action for rules the agent must not violate (they gate check_forbidden_action); afterwards project_state shows the live state by category. No LLM. Set provenance="user_confirmation" only when the user explicitly confirmed it.

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": {
      "content": "<content>",
      "code_kind": "<code_kind>",
      "project": "<project>"
    },
    "name": "remember_code"
  }
}

Input Schema

Name	Required	Default
`content`	Yes
`project`	Yes
`session`	No	default
`code_kind`	Yes
`namespace`	No
`importance`	No
`provenance`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 12, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations are neutral (non-readonly, non-destructive). The description adds context like 'for the coding-agent views', ties to check_forbidden_action and project_state, and warns 'No LLM', providing useful behavioral hints 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 concise yet packed with essential information, front-loaded with the core action and tags, followed by enumerated categories and usage directives. Every sentence adds value.

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

Completeness3/5

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

While the description covers the critical parameters (code_kind, provenance) and ties to related tools, it omits details on remaining 5 parameters and does not explain return values (no output schema). This is acceptable but not fully complete.

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?

With 0% schema description coverage, the description explains code_kind values and their use, and the provenance parameter. However, content, project, session, namespace, and importance receive no additional explanation, leaving gaps.

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 uses specific verb 'capture' and resource 'CODE memory', with tags 'category + project', distinguishing it from siblings like 'remember' and 'remember_commitment'. The list of valid code_kind values further clarifies purpose.

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 using forbidden_action for rules that gate check_forbidden_action and setting provenance only on user confirmation. However, it does not contrast with alternatives like 'remember' or 'remember_commitment'.

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