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Deep Research MCP Server

Deep Research MCP Server

by SECRET4422
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

search_web

Search the web via DuckDuckGo to find relevant information. Specify query, result count, and time filter to tailor research results.

Instructions

Search web via DuckDuckGo HTML (no API key)

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_web"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNo
queryYesSearch query
timeFilterNoall

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.3.1
    • removedInput schema / properties / count / description
      Removed value: -"Number of results (1-10)"
    • changedInput schema / properties / query / description
      Previous value: -"Search query, be specific"New value: +"Search query"
    • removedInput schema / properties / timeFilter / description
      Removed value: -"Time filter appended to query if needed"
  2. First observedv1.2.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries the burden of disclosing behaviors. It only mentions 'no API key,' omitting important traits like rate limits, result format, or limitations of scraping DuckDuckGo HTML. This is insufficient for an agent to understand behavioral implications.

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

Conciseness3/5

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

The description is very concise (one sentence) and front-loaded, but it sacrifices completeness. Every word earns its place, but the overall structure is minimal, lacking the substance needed for a 3-parameter tool.

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?

Given 3 parameters, no output schema, and no annotations, the description is severely incomplete. It fails to explain return format, pagination, error handling, or limitations, leaving critical gaps for an AI agent to correctly invoke the tool.

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 only 33% (only 'query' has a description). The description adds no information about 'count' or 'timeFilter' parameters, failing to compensate for the schema's lack of detail. The agent must infer parameter usage from names alone.

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 the action (Search web) and the specific source (DuckDuckGo HTML) plus a key feature (no API key required). However, it does not differentiate from sibling tools like deep_research or fact_check_claim, missing explicit guidance on when this tool is appropriate.

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. There is no mention of context, prerequisites, or exclusions, leaving the agent without direction for tool selection.

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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