fetch
Fetch full document content for a search result.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| document_id | No |
Fetch full document content for a search result.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | ||
| document_id | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full burden. It only states the basic function without disclosing side effects, permissions, read-only nature, or behavior when parameters are missing (both are optional). This is insufficient for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, well-structured and easy to read. However, it is under-specified, so it does not fully earn its place by providing necessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations, no output schema, and a minimal schema, the description should compensate. It does not mention return format, error handling, or parameter usage, making it incomplete for an agent to rely on.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has two parameters (id and document_id) with no descriptions, and the description does not explain them. With 0% schema coverage, the description fails to add any meaning about how to pass the search result identifier or which parameter to use.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches full document content for a search result, using a specific verb and resource. However, it does not distinguish itself from sibling read/download tools like read_arxiv_paper or download_full_paper_arxiv, which also fetch content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, such as needing a search result ID, nor any exclusions or preferred contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools appear to serve the same purpose, such as search_arxiv and search-arxiv, or papers-search-basic, paper-search-advanced, search_papers, and search. The download/read tools for different sources follow similar patterns, but some return 'not supported' messages, making it unclear which tools are actually functional.
Tool names mix snake_case, kebab-case, and bare verbs without a consistent pattern. For example, about_nanci, analysis-citation-network, download-full-paper-arxiv, fetch, and search_arxiv all coexist, and the same action for different sources alternates conventions (search-arxiv vs search_arxiv).
With 53 tools, the server is heavily over-scoped. Many tools are redundant or near-duplicates, such as six source-specific search tools plus an aggregate search, and the inclusion of both paper and clinical trial tools in one server creates unnecessary bloat.
The server covers a wide range of research workflows, including search, download, read, citations, authors, and clinical trials. However, several tools (crossref/pubmed download/read) are non-functional dead ends, and the redundancy makes it harder to navigate the surface.