Search DBLP computer science bibliography for publications or authors. Free, no key required.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | Publication search query | transformer attention |
| limit | No | Number of results (max 25) | |
| author | No | Search by author name instead of publication title |
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?
With no annotations, the description carries the full burden. It mentions 'Free, no key required' which is a positive behavioral trait, but it does not disclose whether the tool is read-only, rate limits, or any other behavioral details. For a search tool, such information is important.
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 extremely concise: a single sentence that front-loads the action. Every word adds value, with no superfluous information.
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 three parameters and no output schema, the description is somewhat minimal. It covers the basic purpose but lacks details on return format, pagination (though limit is mentioned), and when to use this tool over siblings. It is adequate but not complete.
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?
Schema coverage is 100% as all three parameters have descriptions. The tool description adds context about searching for publications or authors, which aligns with the author parameter, but does not provide additional parameter-specific meaning beyond what the schema already offers.
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 searches DBLP for publications or authors, using a specific verb and resource. It also notes it's free and requires no key, which adds clarity. However, it does not explicitly differentiate from sibling tools like get_ai_papers or search_arxiv_ai.
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. The description only states what it does, without any when-to-use or when-not-to-use information.
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.
Each tool targets a distinct data source: HuggingFace Papers, arXiv, and DBLP. Their purposes are clearly differentiated by source and search type, with no overlap.
All names use lowercase and underscores, but one uses 'get' while two use 'search', creating a slight inconsistency. Otherwise, the pattern is clear.
Three tools is appropriate for a research papers server, covering three major sources without being too few or too many.
The server covers searching across three key AI/ML databases, which is adequate for discovery. Minor gaps exist, such as the lack of a tool to fetch paper details by ID.