Academic Research MCP Server
Server Details
MCP server for academic research data including scholarly papers, citations, research trends, and publication metadata for AI agents.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.1/5 across 2 of 2 tools scored.
The two tools target distinct data sources (arXiv vs Google Scholar) with no functional overlap, making selection unambiguous.
Both tools follow the identical verb_noun snake_case pattern using the 'search_' prefix, creating perfect predictability.
With only 2 tools, the set feels thin for the broad 'Academic Research' domain, falling into the borderline category where the surface is technically functional but noticeably under-scoped.
The server only covers discovery (search) but lacks critical research lifecycle operations like downloading papers, extracting content, or citation management, creating significant workflow dead ends.
Available Tools
2 toolssearch_arxivBRead-onlyInspect
Search the arXiv preprint repository for peer-reviewed academic papers in physics, mathematics, computer science, and related fields. Returns paper title, author list, abstract, publication date, PDF link, and category classification. Use for cutting-edge research, literature review, or staying current in academic fields.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Research keywords or topic (e.g. 'neural networks', 'quantum computing', 'protein folding') | |
| max_results | No | Number of papers to return (default 10, higher values for comprehensive literature review) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return structure (titles, authors, abstracts, PDF links) which compensates for missing output schema, but omits rate limits, pagination behavior, or indexing delays.
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?
Two sentences, front-loaded with purpose then output; no wasted words.
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?
Minimally adequate for a simple search tool; covers output format but misses parameter semantics and sibling differentiation.
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?
With 0% schema description coverage, description fails to compensate by explaining query syntax or max_results constraints/default.
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?
Clear verb (Search) and resource (arXiv), but fails to distinguish from sibling tool search_google_scholar.
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 on when to use arXiv versus Google Scholar or other alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_google_scholarBRead-onlyInspect
Query Google Scholar for academic papers, citations, and research articles across all disciplines. Returns paper title, authors, publication venue, citation count, abstract preview, and full-text link if available. Use for comprehensive literature searches, citation tracking, or finding highly-cited works.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search terms or research topic (e.g. 'machine learning bias', 'climate change economics', 'gene therapy advances') | |
| max_results | No | Maximum papers to retrieve (default 10, recommended for focused results) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return values (titles, authors, citations, links) which is necessary given no output schema exists, but omits other behavioral traits like rate limits or result ordering.
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?
Appropriately brief and front-loaded; two sentences efficiently cover purpose and return values without redundancy, though parameter details are missing.
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?
Adequate for a simple tool with no output schema, but incomplete due to missing parameter explanations and sibling differentiation given the low schema coverage.
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 has 0% description coverage, yet the description fails to explain either parameter ('query' or 'max_results'), leaving agents to infer semantics from property names alone.
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?
Clear verb ('Search') and resource ('Google Scholar'), but fails to explicitly differentiate from sibling 'search_arxiv' (e.g., coverage of published vs preprint literature).
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?
Provides no guidance on when to use this tool versus the 'search_arxiv' sibling or other alternatives.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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