mcp-registry/io.github.laibniz/scholarfetch · v1.12.4
Also listed as glama/laibniz/scholarfetch
As of 2026-10-18 13:02 UTC, the Laibniz Scholarfetch MCP server is up with a Glimind reliability score of 78/100 (grade B). Over the last 30 days it answered 99.5% of Glimind's liveness checks. It had 20 outages in 90 days, with a median recovery of 7 minutes.
Multi-engine scholarly research server for search, traversal, full text, and reading lists.
Claude Code
claude mcp add --transport http laibniz-scholarfetch-mcp-server https://laibniz-scholarfetch-web.hf.space/mcp/
Claude Desktop · Windsurf · Cline (mcpServers JSON)
{
"mcpServers": {
"laibniz-scholarfetch-mcp-server": {
"type": "http",
"url": "https://laibniz-scholarfetch-web.hf.space/mcp/"
}
}
}
Third-party server, listed as discovered. Review its source before installing.
48 parameter(s) across 12 tool(s) have no description.
Add a "description" to each parameter with its format and an example ("ISO 8601 date, e.g. 2026-10-17"). This is the commonest cause of wrong arguments on the first call. How to fix →
12 of 12 tool(s) carry no readOnlyHint/destructiveHint annotations.
Annotate read-only tools with {"readOnlyHint": true}. Agents and gateways can then run them without a confirmation prompt, and route around destructive ones. How to fix →
1 tool(s) look like they change state (create/send/delete/pay…) but declare no destructiveHint.
Set annotations {"readOnlyHint": false, "destructiveHint": true|false, "idempotentHint": …}. Clients use these to ask the user before a side effect and to auto-approve safe reads. How to fix →
Handshake + tools/list takes ~1,843 ms.
Serve tools/list from memory, keep the process warm, and host close to your users. Every new agent session pays this before its first call.
Paste-ready definitions with the problems above fixed. Changes marked verify need a human look. 12 tool(s) still need parameter descriptions written by someone who knows the API. All of them as JSON: /v1/readiness/mcp-registry%2Fio.github.laibniz%2Fscholarfetch/fixes
{
"name": "scholarfetch_doi_lookup",
"description": "Enrich one known DOI with metadata, reading links, and full-text availability signals. If you pass `engines`, use a comma-separated subset of: elsevier, openalex, crossref, arxiv, europepmc, springer, semanticscholar.",
"inputSchema": {
"type": "object",
"title": "scholarfetch_doi_lookupArguments",
"required": [
"doi"
],
"properties": {
"doi": {
"type": "string",
"title": "Doi"
},
"engines": {
"type": "string",
"title": "Engines",
"default": ""
}
}
},
"annotations": {
"readOnlyHint": true
}
}{
"name": "scholarfetch_saved_add",
"description": "Add one paper to a named in-memory reading list on the MCP server. Best input is paper_json copied from another ScholarFetch tool result, but DOI, query+result_index, or author_name+candidate_index+paper_index also work. Reuse the same collection name across calls to keep one research session together.",
"inputSchema": {
"type": "object",
"title": "scholarfetch_saved_addArguments",
"properties": {
"doi": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Doi",
"default": null
},
"query": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Query",
"default": null
},
"engines": {
"type": "string",
"title": "Engines",
"default": ""
},
"collection": {
"type": "string",
"title": "Collection",
"default": "default"
},
"paper_json": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Paper Json",
"default": null
},
"author_name": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"title": "Author Name",
"default": null
},
"paper_index": {
"type": "integer",
"title": "Paper Index",
"default": 1
},
"result_index": {
"type": "integer",
"title": "Result Index",
"default": 1
},
"candidate_index": {
"type": "integer",
"title": "Candidate Index",
"default": 1
}
}
},
"annotations": {
"readOnlyHint": false,
"destructiveHint": false,
"idempotentHint": false
}
}{
"name": "scholarfetch_saved_export",
"description": "Export the current reading list as citations, abstracts, BibTeX, or an aggregated full-text corpus. Valid `format` values: citations, abstracts, bib, fulltext. Valid `style` values when `format=citations`: harvard, apa, ieee. Use `include_references=true` with `format=fulltext` when you want a richer downstream synthesis corpus.",
"inputSchema": {
"type": "object",
"title": "scholarfetch_saved_exportArguments",
"properties": {
"style": {
"type": "string",
"title": "Style",
"default": "harvard"
},
"format": {
"type": "string",
"title": "Format",
"default": "citations"
},
"engines": {
"type": "string",
"title": "Engines",
"default": ""
},
"collection": {
"type": "string",
"title": "Collection",
"default": "default"
},
"include_references": {
"type": "boolean",
"title": "Include References",
"default": false
}
}
},
"annotations": {
"readOnlyHint": true
}
}Get an email or webhook when this server's readiness drops by 10+ points, tool-poisoning text appears, or a tool breaks:
curl -X POST https://glimind.com/v1/subscriptions -H 'content-type: application/json' -d '{"tools":["mcp-registry/io.github.laibniz/scholarfetch"],"email":"[email protected]"}'Agents: watch_tool({"toolId": "mcp-registry/io.github.laibniz/scholarfetch"}) over MCP.
scholarfetch_saved_add ~318 tokensscholarfetch_author_papers ~290 tokensscholarfetch_article_text ~258 tokensscholarfetch_references ~230 tokensscholarfetch_saved_export ~228 tokensStatic checks of the advertised tools/list (schema, descriptions, annotations, tool-poisoning patterns, names, size) plus observed protocol, uptime, latency and contract changes. Read-only: no tool is ever called. Weights: schema 15, docs 20, safety 15, efficiency 15, compatibility 15, protocol 5, reliability 10, stability 5. Token counts are estimates (~3.6 characters per token).
Operator? Fix these, then re-check live. Embed the readiness badge:
[](https://glimind.com/server/mcp-registry%2Fio.github.laibniz%2Fscholarfetch?ref=badge)
<a href="https://glimind.com/server/mcp-registry%2Fio.github.laibniz%2Fscholarfetch?ref=badge"><img src="https://glimind.com/v1/readiness/badge/mcp-registry%2Fio.github.laibniz%2Fscholarfetch.svg" alt="MCP agent-readiness"></a>
.. image:: https://glimind.com/v1/readiness/badge/mcp-registry%2Fio.github.laibniz%2Fscholarfetch.svg :target: https://glimind.com/server/mcp-registry%2Fio.github.laibniz%2Fscholarfetch?ref=badge :alt: MCP agent-readiness
Glimind records every version of this server's tool definitions in a signed, append-only transparency log. Current manifest sha256:d04bcb4e663d39d5…, first seen 2026-10-17, included at leaf 2861 of 21,993. Version history · verify what your client received.
Compare: most reliable files servers · most reliable knowledge servers · most reliable search servers · most reliable retrieval servers
Glimind tells agents whether a server is up right now and how to call it, then fails over to a live alternative when it isn't.
Claude Code
claude mcp add --transport http glimind https://glimind.com/mcp
Claude Desktop · Windsurf · Cline (mcpServers JSON)
{
"mcpServers": {
"glimind": {
"type": "http",
"url": "https://glimind.com/mcp"
}
}
}
As of 2026-10-18 13:02 UTC, the Laibniz Scholarfetch MCP server is up with a Glimind reliability score of 78/100 (grade B). Over the last 30 days it answered 99.5% of Glimind's liveness checks. It had 20 outages in 90 days, with a median recovery of 7 minutes.
Laibniz Scholarfetch MCP server advertises 25 tools, including export_abstracts, export_bibtex, export_citations, export_fulltext, get_abstract.
Point your MCP client at this streamable-http endpoint: https://laibniz-scholarfetch-web.hf.space/mcp/
Glimind scanned all 12 tool definitions for tool-poisoning patterns — hidden or invisible characters, instructions that override the model, concealment from the user, requests to read credential or MCP config files, conversation exfiltration and cross-tool shadowing — and found none. This checks what the server tells the model, not what its code does; review the source before granting access to sensitive data.
Status page: 90-day uptime, every outage and how long it lasted.
Claim this listing to get the Verified operator marker, a remediation checklist and owner analytics, or embed the live badge from any of the tool pages above. Maintainers: alerts, deploy attestation and monthly reports.
Status is an automated estimate from Glimind's liveness checks (handshake and tool listing only; no tool is ever called) and may lag or differ from your network. Glimind is not affiliated with this server or its operator. Operator? Request a correction or opt out at https://glimind.com/opt-out.