MCP-Upstage-Server (UpstageAI/mcp-upstage-server) is an MCP server listed on the M8ven Trust Index. It scores 52 out of 100, grade D. It declares 6 tools. No publisher has claimed this listing.

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D
Caution
52/100

MCP-Upstage-Server

Enables document processing through Upstage AI services including parsing various document formats, extracting structured information with custom schemas, auto-generating extraction schemas, and classifying documents into categories.

→ UpstageAI/mcp-upstage-server· listed on glama

Caution. Specific findings reduced this grade. They are listed on the page. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

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Who stands behind it

UpstageAI

Source: Glama

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Install from

Glamanot scored here

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
⚠️
Known vulnerabilities in dependencies: 16 high
Affects packages this MCP installs at runtime. Upgrade or remove the affected dependency.
✅
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
🔐
You'll be asked for 1 credential: UPSTAGE_API_KEY
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// tools this server exposes4 tools

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

parse_document

Parse a document using Upstage AI's document digitization API. This tool extracts the structure and content from various document types, including PDFs, images, and Office files. It preserves the original formatting and layout while converting the document into a structured format. Supported f…

extract_information

Extract structured information from documents using Upstage Universal Information Extraction. This tool can extract key information from any document type without pre-training. You can either provide a schema defining what information to extract, or let the system automatically generate an appr…

generate_schema

Generate an extraction schema for a document using Upstage AI's schema generation API. This tool analyzes a document and automatically generates a JSON schema that defines the structure and fields that can be extracted from similar documents. The generated schema can then be used with the extract…

classify_document

Classify a document into predefined categories using Upstage AI's document classification API. This tool analyzes a document and classifies it into one of several predefined categories such as invoice, receipt, contract, CV, bank statement, and others. You can use the default classification schem…

// known CVEs in dependencies16 high5 medium9 low

Disclosed vulnerabilities in this server's declared npm dependencies (via OSV). Whether each is reachable depends on the installed versions.

high@modelcontextprotocol/sdk@1.17.4GHSA-345p-7cg4-v4c7

@modelcontextprotocol/sdk has cross-client data leak via shared server/transport instance reuse

high@modelcontextprotocol/sdk@1.17.4GHSA-8r9q-7v3j-jr4g

Anthropic's MCP TypeScript SDK has a ReDoS vulnerability

high@modelcontextprotocol/sdk@1.17.4GHSA-w48q-cv73-mx4w

Model Context Protocol (MCP) TypeScript SDK does not enable DNS rebinding protection by default

highaxios@1.7.9GHSA-35jp-ww65-95wh

axios Vulnerable to Full Man-in-the-Middle via Prototype Pollution Gadget in `config.proxy`

highaxios@1.7.9GHSA-3g43-6gmg-66jw

axios Vulnerable to Credential Theft and Response Hijacking via Prototype Pollution Gadget in Config Merge

Depend on this server? Get alerted when its CVEs change.Watch this server free →
// environment variables
To run this server yourself, you supply these values. They go in your own MCP client configuration and stay on your machine. The secret label means the value is sensitive, not that the server mishandles it.
🔐 secretUPSTAGE_API_KEYEdit .env and add your
// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

6/6 tools missing one or more hints — parse_document (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); extract_information (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); generate_schema (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +3 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

License file

No license file

Add a LICENSE file (MIT, Apache-2.0, etc.).

Tests exist

No test files found

Add tests that exercise each declared tool.

Production dependencies are patched

0 critical, 16 high severity in production deps — @modelcontextprotocol/sdk@1.17.4 (high), @modelcontextprotocol/sdk@1.17.4 (high)

Run npm audit fix, or upgrade the affected packages to a non-vulnerable version.

Dependency freshness

1/7 production deps stale: retry@2022-06-26 (4.1y)

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 5 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
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commit: 5481dcc5ceef83170afe697c1b083fa037646b73
code hash: 393ca247b891f81003c0c356a6bf9ea0822b752f0e2be5d5426e4caecd774a6e
view raw JSON →
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