openai-search-mcp (lie5860/openai-search-mcp) is an MCP server listed on the M8ven Trust Index. M8ven has not graded it: we have no way to read this server ourselves. No publisher has claimed this listing.

C
Caution
74/100
2 months ago

openai-search-mcp

Enables Claude to perform real-time web searches and fetch web page content via MCP, using OpenAI-compatible APIs with optional Tavily or Firecrawl engines.

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

lie5860

Source: Glama

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// key findings
⚠️
Known vulnerabilities in dependencies: 1 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.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
🔐
You'll be asked for 3 credentials: FIRECRAWL_API_KEY, OPENAI_API_KEY, TAVILY_API_KEY
These are read from process.env at runtime. Make sure you trust where they’ll be sent.
// known CVEs in dependencies1 high

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

high@modelcontextprotocol/sdk@1.25.2GHSA-345p-7cg4-v4c7

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

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.
configFETCH_ENGINESet =tavily and Tavily keys so that when fetch_engine is not passed, Tavily is used.
🔐 secretFIRECRAWL_API_KEY"": "your-firecrawl-api-key",
configFIRECRAWL_API_URL"": "https://api.firecrawl.dev/v2"
🔐 secretOPENAI_API_KEYYour API key for that endpoint
configOPENAI_API_URLYour API endpoint URL (e.g., https://api.openai.com/v1)
configOPENAI_DEBUG
configOPENAI_LOG_LEVELLog level No INFO
configOPENAI_MODELThe model identifier (default: gpt-4o)
🔐 secretTAVILY_API_KEY"": "tvly-your-tavily-key",
configTAVILY_API_URL"": "https://api.tavily.com"
// 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

5/5 tools missing one or more hints — web_search (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); web_fetch (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); get_config_info (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +2 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.

Tool inputs are validated

4/5 tool handlers declare input schemas (80%)

Declare an inputSchema with zod/joi/yup on every tool definition.

Tool handlers catch errors

Only 2/5 tool handlers wrap calls in try/catch (40%)

Wrap each tool handler body in try/catch and return a structured error response.

Tests exist

No test files found

Add tests that exercise each declared tool.

Production dependencies are patched

0 critical, 1 high severity in production deps — @modelcontextprotocol/sdk@1.25.2 (high)

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

Dependency freshness

1/4 production deps stale: node-fetch@2023-11-30 (2.6y)

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 6 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: 7cd849e966528ee85bdde6e0f000395124c32133
code hash: 57c4264c981e3f2b27916314c5d03203f9454bc4b297c6ffe667a4a803618c53
verified: 6/22/2026, 12:46:43 PM
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