A
license-
qualityC
maintenanceVerifies citations in reference lists by checking DOIs against public registries to catch AI-hallucinated or mismatched citations.
MIT
OpenWarrant — Reference Verification
by sh.stipple
Server Details
Fact-check citations: resolve, match, support claims; math rechecked. No API key — URL in.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
MCP client
Glama
MCP server
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
100% free. Your data is private.
Tool Definition Quality
A4.8/5.0
Tool DescriptionsA
Average 4.8/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
Only one tool exists, so there is no possibility of ambiguity. The tool's purpose is clearly defined.
Naming Consistency5/5
With a single tool, naming is consistent by default. The name 'verify_references' is clear and follows a verb_noun pattern.
Tool Count4/5
One tool for a narrow domain is borderline thin, but the tool is comprehensive and well-scoped for reference verification, so it is reasonable.
Completeness5/5
The tool covers all aspects of reference verification: input methods (URL, text, base64), citation resolution, math checking, deep evidence fetching, and provides a shareable report. No obvious gaps for its stated purpose.
Available Tools
1 toolverify_referencesAInspect
Fact-check a document's REFERENCES and CLAIMS — built for AI-generated reports whose citations must be checked before they're trusted.
USE THIS WHEN someone shares a report, article, whitepaper, or deep-research export (or a
link to one) and asks: is this accurate / legit? are these citations real? fact-check this.
did the AI make this up? Also use it proactively before relying on any AI-written document.
Provide the document ONE way: `url` (a public http(s) link to a PDF or web page — fetched
server-side, the cheapest call: no need to download or encode anything), `text` (pasted
markdown/plain prose), OR `bytes_b64` (a base64 PDF; URLs are read from the PDF's link
annotations, so they're exact). Default (fast): provenance (is it a ChatGPT deep-research
export?), citation resolution (live / archived / dead, papers matched against arXiv/Crossref
to catch 'real ID, wrong paper'), and internal MATH (recompute the doc's own arithmetic).
Set `deep=true` to also fetch each cited source and judge whether it SUPPORTS or CONTRADICTS
the claim (slower, ~a minute).
Returns a trust summary, per-item tables, and a shareable `permalink` to the public
fact-check record. HONEST BOUNDARY: this reports verification COVERAGE, not truth —
'supported' means evidence-backed (not necessarily true) and 'unsupported' means no evidence
found (not necessarily false). It tells a reviewer WHERE to look; it does not bless the
document, and it never affects the fraud risk band.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | ||
| deep | No | ||
| text | No | ||
| filename | No | document.pdf | |
| bytes_b64 | No |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A4.8/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully bears the burden. It explains the three default checks (provenance, citation resolution, math) and the deep mode. Crucially, it provides an honest boundary: it reports verification coverage, not truth, and tells the reviewer where to look without blessing the document or affecting fraud risk.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is longer than average but well-structured: opening purpose, usage guidelines, input options, capabilities, and honesty note. It is front-loaded with the core action and use cases. Every sentence adds value, though it could be slightly trimmed without losing substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given five parameters, zero schema descriptions, no annotations, and an output schema (not detailed), the description covers the essential: inputs, outputs (trust summary, tables, permalink), and behavioral boundaries. It lacks explicit error handling or rate limits but is sufficiently complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description compensates effectively. It explains all five parameters: url (public http link, server-side fetched, cheapest), text (pasted markdown/prose), bytes_b64 (base64 PDF, exact URLs from link annotations), filename (default 'document.pdf'), and deep (boolean, slower but fetches sources). Every parameter gets meaningful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: fact-check a document's references and claims. It specifies the target use case (AI-generated reports) and uses strong verbs like 'verify' and 'fact-check'. It distinguishes itself from generic search tools by focusing on citation verification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises when to use this tool: when someone asks about accuracy, legitimacy, or AI hallucination of citations. It also suggests proactive use before trusting AI-written documents. It outlines three input methods with cost implications, helping the agent choose wisely.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Servers
- Alicense-qualityFmaintenanceVerifies claims with verdicts (supported/disputed/unverifiable), confidence scores, and cited sources by cross-referencing FoundryNet Data Network and web search.MIT
- Alicense-qualityBmaintenanceEnables per-claim citation verification for AI-generated text by fetching cited sources and judging whether they support the claim, with verdicts and evidence quotes.66MIT
- Alicense-qualityBmaintenanceToken cost math for LLM API calls: current per-million-token rates for 69 models across 17 providers, with local arithmetic for estimates, comparisons and monthly budgets. Rates are verified and date-stamped.412MIT