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Deep Research MCP Server

Deep Research MCP Server

by SECRET4422
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

memory_search

Search stored research memory to retrieve relevant information. Use a query with optional tags and limit results to find previous research data.

Instructions

Search memory

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": "memory_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
tagsNo
limitNo
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.3.1
    • removedInput schema / properties / limit / description
      Removed value: -"Max results"
    • removedInput schema / properties / query / description
      Removed value: -"Search query in keys/values/tags"
    • removedInput schema / properties / tags / description
      Removed value: -"Filter by tags (any match)"
  2. First observedv1.2.0

TDQS

D1.5/5.0
Behavior1/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits like read/write nature, authentication needs, or rate limits. It says nothing beyond the literal operation, offering no transparency.

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

Conciseness2/5

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

While extremely concise at two words, the description is underspecified and lacks necessary information, making it inefficient for agent understanding. It prioritizes brevity over clarity.

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

Completeness1/5

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

For a tool with 3 parameters, no output schema, and no annotations, the description is woefully incomplete. It fails to convey return behavior, pagination, or any context needed for correct usage.

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

Parameters1/5

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

Schema description coverage is 0% and the description fails to explain the meaning or usage of any of the three parameters (tags, limit, query). It does not add value beyond the raw schema.

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

Purpose2/5

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

The description 'Search memory' is a tautology that merely restates the tool name 'memory_search' without specifying the resource or scope. It fails to distinguish from sibling tools like search_web or memory_save.

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?

The description provides no guidance on when to use this tool versus alternatives such as deep_research or memory_save. No contexts, exclusions, or prerequisites are mentioned.

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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