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Search and read in one call

research
Read-only

Search the web, fetch top pages, and return a citable brief with source references in one call.

Instructions

One-shot research: search the web, fetch the top results, return both.

Best for:
- Open-ended questions that need finding sources AND reading them
  ("what's new with X", "summarize the controversy around Y").
- Replacing a `search` + N x `fetch` chain with one call.
- Producing a citable brief with [n]-style source references.

Not recommended for:
- You only need links -> `search` (cheaper, no fetching).
- You only need to read one URL you already have -> `fetch`.
- You want to query previously-fetched cached pages -> `cache_search`.
- Checking or expanding one paper's citations -> `paper_graph`.

Returns:
- markdown (default): a "Research brief" with a Sources index then the
  full Markdown body of each fetched document, separated by horizontal
  rules; includes a token estimate.
- json: {question, engines, sources:[{rank,title,url,snippet,...}],
  documents:[...], tokens_estimated, errors}.

Common mistakes:
- Using `depth=8` for a quick lookup: that's 8 page fetches, and 2-3 is
  almost always enough.
- Calling `research` for a known URL: that is what `fetch` is for.
- Forgetting that `fetch=False` returns sources only (much cheaper if
  the LLM only needs to pick which one to read).

Args:
    question: What you want to know, in natural language.
    depth: How many top results to fetch (1-8). 3 is a good default.
    engines: Override the engine set (see `engines()` for names). Prefer
        `category=`. Naming engines turns category routing off.
    fetch: If False, return source list without reading them.
    freshness: "day"|"week"|"month"|"year". Restricts to recent results.
        Best-effort; undated results are kept rather than dropped.
    include_domains: Restrict to these domains (e.g. ["python.org"]).
    exclude_domains: Drop results from these domains.
    category: Which KIND of source to search; a bare group widens, a dotted
        sub-group narrows. Same values as `search`; see `engines()`.
    include_text: Substring required in title or snippet (case-insensitive).
    exclude_text: Substring forbidden in title or snippet.
    use_cache: Reuse cached search/page data within TTL.
    max_age_hours: Treat cached search results AND cached page bodies older
        than this as a read miss; fresh data is always written back. 0 =
        force-refresh both the engine search and every fetched page body;
        None = server default TTL (7 days). A non-zero value is honored for
        both halves (it used to be ignored for anything but 0).
    format: "markdown" or "json".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
fetchNo
formatNomarkdown
enginesNo
categoryNo
questionYes
freshnessNo
use_cacheNo
exclude_textNo
include_textNo
max_age_hoursNo
exclude_domainsNo
include_domainsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.12.0
    • changedInput schema / properties / category / anyOf
      Previous value: -[
      -  {
      -    "enum": [
      -      "news",
      -      "pdf",
      -      "github",
      -      "paper",
      -      "forum",
      -      "blog",
      -      "image",
      -      "dataset"
      -    ],
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "enum": [
      +      "news",
      +      "pdf",
      +      "github",
      +      "paper",
      +      "forum",
      +      "blog",
      +      "image",
      +      "dataset",
      +      "finance",
      +      "software",
      +      "security",
      +      "reference",
      +      "weather",
      +      "docs",
      +      "gov",
      +      "stats",
      +      "calendar",
      +      "news.world",
      +      "paper.index",
      +      "paper.preprint",
      +      "paper.biomed",
      +      "paper.cs",
      +      "paper.math",
      +      "paper.openaccess",
      +      "paper.trial",
      +      "dataset.repository",
      +      "dataset.ml",
      +      "dataset.gov",
      +      "finance.filings",
      +      "finance.market",
      +      "finance.macro",
      +      "finance.fx",
      +      "finance.entity",
      +      "finance.crypto",
      +      "software.lifecycle",
      +      "software.github",
      +      "software.python",
      +      "software.node",
      +      "software.rust",
      +      "software.registry",
      +      "software.app",
      +      "security.cve",
      +      "security.package",
      +      "security.exploited",
      +      "reference.domain",
      +      "docs.web",
      +      "docs.rfc",
      +      "gov.us",
      +      "gov.uk",
      +      "stats.indicator",
      +      "calendar.holidays",
      +      "calendar.clock"
      +    ],
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • changedOutput schema / (root)
      Previous value: -{
      -  "properties": {
      -    "result": {
      -      "anyOf": [
      -        {
      -          "type": "string"
      -        },
      -        {
      -          "additionalProperties": true,
      -          "type": "object"
      -        }
      -      ],
      -      "title": "Result"
      -    }
      -  },
      -  "required": [
      -    "result"
      -  ],
      -  "title": "researchOutput",
      -  "type": "object"
      -}New value: +null
  2. Changed1 schema field changedv0.9.1
    • changedInput schema / properties / category / anyOf
      Previous value: -[
      -  {
      -    "enum": [
      -      "news",
      -      "pdf",
      -      "github",
      -      "paper",
      -      "forum",
      -      "blog"
      -    ],
      -    "type": "string"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "enum": [
      +      "news",
      +      "pdf",
      +      "github",
      +      "paper",
      +      "forum",
      +      "blog",
      +      "image",
      +      "dataset"
      +    ],
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
  3. First observedv0.1.0

TDQS

A5/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, but the description goes far beyond that: it discloses fetch behavior, cache semantics (use_cache, max_age_hours with 0 vs None), freshness handling, the difference between markdown and json return formats, the effect of fetch=False, and even behavioral nuances like 'Naming engines turns category routing off'. It also explains that non-zero max_age_hours is honored for both halves, correcting a past behavior. This is rich, accurate, and does not contradict the annotations.

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 long but impeccably structured: a one-line summary, then 'Best for', 'Not recommended for', 'Returns', 'Common mistakes', and 'Args' sections. Every sentence adds value—even the 'Common mistakes' section reinforces the usage guidelines. It is front-loaded with the core purpose, and the Args section is efficiently organized with one-line-per-parameter explanations. Nothing is redundant.

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 (13 parameters, no output schema) and the absence of an output schema, the description covers everything an agent needs: return formats (markdown vs json) with descriptions, parameter semantics, usage guidance, and even error handling (json 'errors' field). It also provides token estimates and source structure, making it self-contained for correct invocation.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries full responsibility for parameter meaning. It does this exceptionally: each of the 13 parameters is explained in natural language with defaults, effects, and interactions (e.g., depth=3 as good default, engines override category routing, include_text substring semantics). This far exceeds the schema's basic types and enums.

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 opening line 'One-shot research: search the web, fetch the top results, return both' states a specific verb+resource and a composite action. It distinguishes itself from siblings via the 'Not recommended for' section, naming 'search', 'fetch', and 'cache_search' with explicit conditions. This leaves no ambiguity about what the tool does.

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 'Best for' and 'Not recommended for' sections are explicit, concrete, and name the exact sibling tools to use instead (search, fetch, cache_search, paper_graph) with the conditions that select them. It even gives example use cases and common mistakes (e.g., using depth=8 for quick lookups), leaving no inference to the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.