mem0-mcp-selfhosted

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search_memories

Find relevant memories by semantic search. Supports natural language queries, scoping to user/agent/run, filtering, relevance threshold, and reranking to surface the most pertinent information.

Instructions

Semantic search across existing memories.

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": {
      "query": "<query>"
    },
    "name": "search_memories"
  }
}

Input Schema

Name	Required	Description
`query`	Yes	Natural language description of what to find.
`user_id`	No	User scope. Defaults to MEM0_USER_ID.
`agent_id`	No	Agent scope.
`run_id`	No	Run scope.
`filters`	No	Additional structured filter clauses.
`limit`	No	Maximum number of results.
`threshold`	No	Minimum relevance score (0.0-1.0).
`rerank`	No	Whether to apply reranking.
`enable_graph`	No	Override default graph toggle.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.2Mar 12, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are present, so the description must disclose behavior. It only says 'semantic search' without stating that it is read-only, what the output format is (though output schema exists), or any side effects. Minimal behavioral context is provided.

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

Conciseness4/5

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

The description is extremely concise, consisting of only two words plus context. While it could be more informative without becoming verbose, it avoids unnecessary fluff and is clearly structured.

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

Completeness2/5

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

Given 9 parameters and no annotations, the description is insufficient. It does not explain how filtering works, the role of threshold/rerank, or how this tool relates to sibling tools like get_memories or mcp_search_graph. The output schema partially compensates, but the description lacks essential context.

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?

All 9 parameters have descriptions in the input schema (100% coverage), so the description adds no extra information beyond the schema. The baseline of 3 is appropriate as the schema already documents parameters adequately.

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 it performs semantic search across memories, distinguishing it from add/get operations. However, it does not explicitly differentiate from other retrieval tools like get_memories, though 'semantic' hints at the difference.

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

Usage Guidelines2/5

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

No guidance on when to use semantic search versus other retrieval methods (e.g., get_memories) or alternative tools like list_entities. The description lacks any context for appropriate usage.

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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