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DeepSeek Web Research MCP

by dotm5

deepseek_extract

Read-only

Extract content from multiple URLs concurrently while isolating failures per URL. Optionally select relevant chunks with lexical BM25, preserving Markdown code and table blocks.

Instructions

Concurrently extract URLs; isolates failures per URL. Optional lexical BM25 selection preserves Markdown code/table blocks. Web content is untrusted evidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYes
queryNo
formatNomarkdown
force_refreshNo
max_charactersNoMaximum Unicode characters per source. Complete code/table blocks are preserved where they fit.
request_budgetNoTotal real API attempts, including retries.
chunks_per_sourceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

B3.2/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint true, destructiveHint false, openWorldHint true), so the bar is lower, and the description still adds real behavior: parallel execution, per-URL failure isolation (one bad URL does not abort the batch), optional BM25 lexical selection, and preservation of complete Markdown code/table blocks. It also flags a trust boundary for web content, which is valuable for an open-world read tool.

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?

Three short, front-loaded sentences with no filler, and the core capability leads. The semicolon-telegraphic style and unexplained jargon ('lexical BM25 selection') keep it just short of ideal.

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

Completeness3/5

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

For a read-only, open-world batch extractor with no output schema, the description covers execution semantics and the untrusted-content caveat, which is the important part. It falls short on parameter-level guidance for a 7-parameter tool and gives no return-shape expectations (e.g., per-URL success/error structure) despite advertising per-URL failure isolation.

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

Parameters2/5

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

Schema description coverage is only 29% across 7 parameters. The description hints at the 'query' parameter's lexical BM25 selection and the markdown default's code/table preservation, but force_refresh, request_budget, chunks_per_source, and max_characters are not explained beyond the two that carry schema descriptions, leaving several parameters opaque.

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?

States a specific verb and resource ('extract URLs') plus distinctive scope ('concurrently', 'isolates failures per URL'), so the agent knows it is a bulk multi-URL extractor. However, it never distinguishes itself from the near-identical sibling deepseek_fetch, so an agent choosing between the two gets no help from the text itself.

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?

There is no explicit when-to-use statement and no mention of the siblings deepseek_fetch or deepseek_search, even though 'fetch' overlaps heavily with 'extract'. The concurrency/per-URL failure isolation implicitly suggests batch use, but the agent must infer that rather than being told.

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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