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Desearch-ai

Desearch MCP Server

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by Desearch-ai
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JavaScript
Remote

AI Search

ai-search
Read-only

Search and analyze the web, X, Reddit, Wikipedia, and arXiv via Desearch AI to retrieve relevant links and summaries.

Instructions

AI search and analysis on web using Desearch AI

Input Schema

NameRequiredDescriptionDefault
modelNoModel to use for the search: NOVA (default) or ORBIT.NOVA
toolsNoSource ids sent to POST /desearch/ai/search. Short ids: 'web', 'twitter', 'arxiv', 'wikipedia', 'hackernews', 'reddit'. Legacy labels such as 'Web Search', 'ArXiv Search', 'Wikipedia Search', 'Hacker News Search', and 'Reddit Search' are rewritten to those ids. Example: ['web', 'twitter'].
promptYesQuestion, example: 'What is the latest news on AI?'
end_dateNoEnd of the date range in UTC (YYYY-MM-DDTHH:MM:SSZ). Use with start_date.
start_dateNoStart of the date range in UTC (YYYY-MM-DDTHH:MM:SSZ). Use with end_date.
date_filterNoDeprecated relative window; prefer start_date/end_date. Example: 'PAST_WEEK'
result_typeNoONLY_LINKS returns links only; LINKS_WITH_FINAL_SUMMARY adds an AI summary. Link arrays are kept under whichever key the API uses, along with billing fields. ONLY_LINKS still depends on the API to include those links.
exclude_domainsNoDrop Web Search results from these domains, example: ['pinterest.com']
include_domainsNoRestrict Web Search results to these domains, example: ['bbc.com', 'reuters.com']

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.4
    • changedInput schema / properties / tools / description
      Previous value: -"Source ids sent to POST /desearch/ai/search. Use short ids such as 'web' and 'twitter'. Legacy labels such as 'Web Search' are accepted and rewritten to those ids. Example: ['web', 'twitter']."New value: +"Source ids sent to POST /desearch/ai/search. Short ids: 'web', 'twitter', 'arxiv', 'wikipedia', 'hackernews', 'reddit'. Legacy labels such as 'Web Search', 'ArXiv Search', 'Wikipedia Search', 'Hacker News Search', and 'Reddit Search' are rewritten to those ids. Example: ['web', 'twitter']."
    • changedInput schema / properties / tools / items / enum
      Previous value: -[
-  "web",
-  "twitter",
-  "arxiv",
-  "wikipedia",
-  "youtube",
-  "hackernews",
-  "reddit"
-]New value: +[
+  "web",
+  "twitter",
+  "arxiv",
+  "wikipedia",
+  "hackernews",
+  "reddit"
+]
  2. Changed1 schema field changedv0.1.3
    • changedInput schema / properties / model / description
      Previous value: -"Model to use for the search, example: 'NOVA', Nova is 10s model, Orbit is 30s model"New value: +"Model to use for the search: NOVA (default) or ORBIT."
  3. First observedv0.1.2

TDQS

C2.3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no further behavioral context, such as what the AI analysis returns, whether it incurs billing, or how source selection affects results.

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 a single short sentence with no wasted words, but it is under-informative for a tool of this complexity rather than genuinely concise. It is front-loaded but does not say enough to be useful.

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?

For a 9-parameter search tool with no output schema, the description is severely lacking. It does not explain what the tool returns, how the AI analysis differs from plain search, or how to choose between related sibling tools, leaving the agent to rely entirely on the schema.

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%, and the schema itself thoroughly documents all 9 parameters, including enums, defaults, and date-range semantics. The description adds nothing beyond the schema, so the baseline score of 3 is appropriate.

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 largely restates the title 'AI Search' and adds only a vague brand qualifier, 'using Desearch AI'. It does not specify what kind of analysis is performed or how the tool differs from the sibling 'web-search', which is essential for a search tool with 9 parameters.

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 when-to-use or when-not-to-use guidance is given, and no alternatives are mentioned. The agent cannot tell from the description whether 'ai-search' is preferred over 'web-search' or 'x-search' for any particular query.

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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