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Memstate AI - Agent Memory System

Official

memstate_get

Retrieve stored memories from the Memstate AI Agent Memory System to access existing knowledge before starting tasks, enabling efficient browsing of projects and content.

Instructions

Browse and retrieve memories. Use BEFORE starting tasks to fetch existing knowledge.

USE THIS WHEN: You need to read what's already stored — list projects, browse a project tree, or get content at a keypath. NOT FOR: Saving new content (use memstate_remember for markdown/summaries, memstate_set for one keypath value).

memstate_get() → list all projects memstate_get(project_id="myapp") → full project tree memstate_get(project_id="myapp", keypath="database") → subtree memstate_get(project_id="myapp", keypath="db", include_content=true) → with full content memstate_get(memory_id="mem_abc123") → single memory by ID

Keypath is auto-prefixed. Default recursive=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoProject to retrieve from. If omitted, lists all projects.
keypathNoSubkeypath within project. If omitted with project_id, returns the full project tree.
memory_idNoAlternative: get a single memory by its UUID
recursiveNoInclude subtree (default: true)
include_contentNoIf true, include full memory content in response (not just keypaths)
at_revisionNoOptional revision number for time-travel queries
content_limitNoMax memories to hydrate when include_content=true (default: 200, max: 1000)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `memstate_get` tool is dynamically proxied from a remote Memstate MCP server. The tool call is handled by forwarding the request to the remote client using `remote.callTool`.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      return await remote.callTool({
        name: request.params.name,
        arguments: request.params.arguments,
      });
    });
Behavior4/5

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

With no annotations provided, the description carries full burden and adds valuable behavioral context. It explains that 'Keypath is auto-prefixed' and 'Default recursive=true', which are important behavioral traits not evident from the schema alone. It also provides example usage patterns showing different parameter combinations and their effects.

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 well-structured with clear sections, bullet points for examples, and zero wasted text. Every sentence serves a purpose: establishing context, providing usage guidelines, showing examples, and noting important defaults. It's appropriately sized for a tool with 7 parameters and complex usage patterns.

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

Completeness5/5

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

Given the tool's complexity (7 parameters, multiple usage patterns) and the presence of an output schema, the description is complete. It covers purpose, guidelines, behavioral traits, and provides concrete examples. The output schema existence means the description doesn't need to explain return values, and it adequately addresses the tool's scope and limitations.

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 description coverage is 100%, so the baseline is 3. The description adds some value through the usage examples that show how parameters combine (e.g., project_id alone vs. with keypath, include_content=true), but doesn't provide significant additional semantic meaning beyond what's already documented in 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's purpose: 'Browse and retrieve memories' with specific verbs and resources. It distinguishes from siblings by explicitly contrasting with memstate_remember (for saving markdown/summaries) and memstate_set (for one keypath value), making the distinction clear.

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

Usage Guidelines5/5

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

The description provides explicit guidance: 'Use BEFORE starting tasks to fetch existing knowledge' and includes dedicated 'USE THIS WHEN:' and 'NOT FOR:' sections. It names specific alternatives (memstate_remember, memstate_set) and gives concrete scenarios for when to use this tool (list projects, browse project tree, get content at keypath).

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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