# ScholarFetch

> Multi-engine scholarly research server for search, traversal, full text, and reading lists.

- name: io.github.laibniz/scholarfetch
- version: 0.2.1
- connection class: R0 (autonomous)
- trust: 83/100
- quality: 79/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.laibniz%2Fscholarfetch
- tools: https://api.protogrid.dev/v1/servers/io.github.laibniz%2Fscholarfetch/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "scholarfetch": {
      "type": "http",
      "url": "https://laibniz-scholarfetch-web.hf.space/mcp/"
    }
  }
}
```


## Trust

- hygiene: 100
- liveness: 100
- freshness: 45
- provenance: 80
- drivers: +repository +namespace-matches-repo +reachable +uptime-99% -stale-211d
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 79/100 (good)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-06-18; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 71 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- fail `tools.annotations`: no tool declares readOnlyHint or destructiveHint, so clients cannot tell safe calls from risky ones
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: scholarfetch_author_candidates (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); scholarfetch_author_papers (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); scholarfetch_saved_list (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); …
- pass `tools.token_cost`: about 1,966 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 100 (weight 15)

- pass `stability.changes`: no tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 12, about 1,966 tokens to load them all
- tool set hash: e47e895002abf5cf0a478d661504138f
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.laibniz/scholarfetch.svg)](https://protogrid.dev/servers/io.github.laibniz/scholarfetch)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

_No tool definition changes recorded._

## Remotes

- https://laibniz-scholarfetch-web.hf.space/mcp/ (streamable-http, auth none, reachable true, uptime30d 0.99159664)

## Packages

_none_

## Tools (12)

- `scholarfetch_abstract`: Read the best abstract available for a paper. Use with a DOI or with author_name + candidate_index + paper_index after author_papers. If you pass `engines`, use a comma-separated subset of: elsevier, openalex, crossref, arxiv, europepmc, springer, semanticscholar.
- `scholarfetch_article_text`: Read full paper text when machine-readable content is recoverable. Use with a DOI or with author_name + candidate_index + paper_index. Uses Elsevier first, then open-access fallbacks such as Springer OA, Europe PMC, arXiv PDF, and generic PDF URLs when text is recoverable. If you pass `engines`, use a comma-separated subset of: elsevier, openalex, crossref, arxiv, europepmc, springer, semanticscholar.
- `scholarfetch_author_candidates`: Disambiguate a human author name into ranked identity candidates. Use this before `scholarfetch_author_papers` when the name is ambiguous and you need a stable `candidate_index`. If you pass `engines`, it must include `openalex`.
- `scholarfetch_author_papers`: Expand one author into a deduplicated paper list. This is the main author->paper traversal tool and supports research filters. Use `author_id` when you already know the exact author, or `author_name` plus `candidate_index` after `scholarfetch_author_candidates`. Supported comma-separated `filters`: year>=YYYY, year<=YYYY, year=YYYY, has:abstract, has:doi, has:pdf, venue:<text>, title:<text>, doi:<text>. If you pass `engines`, it must include `openalex`.
- `scholarfetch_doi_lookup`: 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.
- `scholarfetch_references`: Expand a paper into its references. Use with a DOI or with author_name + candidate_index + paper_index. This is the main edge-expansion tool for traversing the literature graph. If you pass `engines`, use a comma-separated subset of: elsevier, openalex, crossref, arxiv, europepmc, springer, semanticscholar.
- `scholarfetch_saved_add`: 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.
- `scholarfetch_saved_clear`: Clear all papers from a named in-memory reading list. Useful when restarting a research branch.
- `scholarfetch_saved_export`: 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.
- `scholarfetch_saved_list`: List all papers currently saved in a named in-memory reading list. Use this to inspect the working set before exporting or removing items.
- `scholarfetch_saved_remove`: Remove one paper from a named in-memory reading list by DOI or exact title.
- `scholarfetch_search`: Start a research traversal from keywords, a DOI, or a person name. Returns deduplicated paper records that you can inspect, save, expand through references, or use as seeds for author exploration. If you pass `engines`, use a comma-separated subset of: elsevier, openalex, crossref, arxiv, europepmc, springer, semanticscholar.