MCP Scholarly Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search-arxivC | Search arxiv for articles related to the given keyword. |
| search-google-scholarC | Search google scholar for articles related to the given keyword. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one searches ArXiv specifically, while the other searches Google Scholar. There is no overlap in their functionality, and an agent can easily choose the appropriate tool based on the desired academic database.
Both tools follow a consistent verb_noun pattern with 'search' as the verb and the database name as the noun (arxiv, google-scholar). The naming is uniform and predictable across the set.
With only 2 tools, the server feels thin for a 'Scholarly Server' that might be expected to handle broader academic tasks. While search is a core function, typical scholarly workflows could benefit from additional tools like fetching article details, citations, or managing references.
The server is severely incomplete for a scholarly domain, as it only provides search functionality without any tools for retrieving full articles, accessing metadata, or performing follow-up actions like citation analysis. This leaves significant gaps that could hinder agent workflows.