Scholar RAG MCP
PYPI · SCHOLAR-RAG-MCP
Academic paper knowledge-base MCP server: PDF ingest, vector search with reranking, KB management.
Available components
Last scanned (15 hours ago)
Scores higher than 89% of PyPI servers
Category Education and Research
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 4 of 47 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency84
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to notwhiteblank/scholar-rag-mcp). View diagnostics → Pass
- Licence could not be checked: the licence is shipped as a file inside the package, not declared as a standard (SPDX) licence identifier, so we cannot tell whether it is OSI-approved.Unverified
- Actively maintained (last published 62 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability59
- AI-judged instruction clarity (fair).Partial
- Tool/resource definitions use about 513 tokens (~46/item across 11 items; 11 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety75
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- 0 of 2 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation; "remove_document" implies "remove" and declares no destructiveHint at all, which the MCP spec reads as destructive by default. See how to fix → Fail
- An AI judge read all 11 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Checks we ran (15)
- Malware scan
- Known CVEs
- Install scripts
- Dependency health
- Source repository
- Provenance
- Maintenance
- Security disclosure
- Schema quality
- Stability
- Tool coverage
- Injection markers
- Destructive annotations
- Judged manipulation
- MCP protocol
Checks we could not complete (1)
These are gaps on our side, not findings about this package. We only credit what we can confirm, so a category made up entirely of them scores 0.
- License in Provenance & TransparencyLicence could not be checked: the licence is shipped as a file inside the package, not declared as a standard (SPDX) licence identifier, so we cannot tell whether it is OSI-approved.
Does not apply to this package (2)
- Endpoint SecurityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
- Transport & ReachabilityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
The score does not measure everything. What the score does not measure →
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Nov 26 +15
- Malware scan: unverified → pass ▲ security
- 1 Nov 26 +1
- Stability: 0.97 → pass security
- 31 Oct 26 −1
- Stability: pass → 0.97 functional
- 30 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 29 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 28 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 25 Oct 26 +1
- Stability: 0.97 → pass security
- 24 Oct 26 −1
- Stability: pass → 0.97 functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 5 Nov 2026 · Analysed pypi/scholar-rag-mcp@0.4.0
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | notwhiteblank/scholar-rag-mcp |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/notwhiteblank/scholar-rag-mcp/.github/workflows/publish.yml@refs/tags/v0.4.0 |
| Rekor log index | 2705871968 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:b2e43037b9b1227d8ab1caeb61e3506d5514a6e1a08d61577d921974a60829c2 |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | Known build tool | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 47 packages
| Packages resolved | 47 |
|---|---|
| Stale | 3 |
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
add_document ~39
Asynchronously ingest a single PDF into an existing kb; returns a job_id.
| Name | Type | Req | Description |
|---|---|---|---|
| kb | string | yes | – |
| pdf_path | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
create_kb ~74
Asynchronously create a kb from all PDFs in a folder; returns a job_id.
| Name | Type | Req | Description |
|---|---|---|---|
| chunk_max | integer | – | – |
| chunk_min | integer | – | – |
| chunk_overlap | integer | – | – |
| folder_path | string | yes | – |
| kb_name | string | yes | – |
| skip_existing | boolean | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
delete_kb ~36
Two-phase kb deletion: preview and confirm token, else full deletion.
| Name | Type | Req | Description |
|---|---|---|---|
| confirm_token | – | – | – |
| kb | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_document ~39
Overview of a document: metadata, abstract, section outline and total character count.
| Name | Type | Req | Description |
|---|---|---|---|
| doc_id | string | yes | – |
| kb | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_document_text ~59
Paginated reading of the full text or a single section of a document.
| Name | Type | Req | Description |
|---|---|---|---|
| doc_id | string | yes | – |
| kb | string | yes | – |
| page | integer | – | – |
| page_size | integer | – | – |
| section | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
get_job ~28
Query the status, progress and result of a background job.
| Name | Type | Req | Description |
|---|---|---|---|
| job_id | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_documents ~46
Paginated browse of documents in a kb.
| Name | Type | Req | Description |
|---|---|---|---|
| kb | string | yes | – |
| page | integer | – | – |
| page_size | integer | – | – |
| sort | string | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
list_kbs ~18
List all knowledge bases with metadata and status.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
remove_document ~37
Synchronously delete a document from qdrant, catalog and disk.
| Name | Type | Req | Description |
|---|---|---|---|
| doc_id | string | yes | – |
| kb | string | yes | – |
Structured output declared, but exposes no named fields.
No examples provided.
search_chunks ~60
Semantic search over chunk bodies of a kb with metadata filters, embedding and rerank scores.
| Name | Type | Req | Description |
|---|---|---|---|
| kb | string | yes | – |
| metadata_filter | – | – | – |
| min_score | – | – | – |
| query | string | yes | – |
| top_k | integer | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
search_documents ~77
Document-level PubMed-style search with optional FTS query and metadata filters.
| Name | Type | Req | Description |
|---|---|---|---|
| authors | – | – | – |
| journal | – | – | – |
| kb | string | yes | – |
| page | integer | – | – |
| page_size | integer | – | – |
| query | – | – | – |
| title | – | – | – |
| year_from | – | – | – |
| year_to | – | – | – |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the Scholar RAG MCP server?
Scholar RAG MCP runs locally as a PyPI package, launched with uvx scholar-rag-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · scholar-rag-mcp
claude mcp add notwhiteblank-scholar-rag-mcp -- uvx scholar-rag-mcp
What is the Scholar RAG MCP server?
Scholar RAG MCP is listed in the public MCP registry as io.github.notwhiteblank/scholar-rag-mcp. Academic paper knowledge-base MCP server: PDF ingest, vector search with reranking, KB management. This page covers its PyPI package (scholar-rag-mcp).
Is the Scholar RAG MCP server safe to use?
Scholar RAG MCP scores 86 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Scholar RAG MCP server expose?
Scholar RAG MCP exposes 11 tools: search_chunks, search_documents, list_documents, get_document, get_document_text, and 6 more. Their descriptions and schemas cost roughly 513 tokens of context every time the server is loaded.
Is the Scholar RAG MCP server still maintained?
Scholar RAG MCP is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What did VerifyMCP test on the Scholar RAG MCP server?
VerifyMCP ran 15 checks on Scholar RAG MCP, covering Malware scan, Known CVEs, Install scripts, Dependency health and 11 more. One item could not be completed, a gap on our side rather than a finding about Scholar RAG MCP: License. Endpoint Security and Transport & Reachability do not apply to a PyPI package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.