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cve-mcp-server

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TypeScript
Remote

Discover CVE proof-of-concepts

cve_get_pocs
Read-onlyIdempotent

Find public proof-of-concept exploits and references for any CVE by aggregating GitHub PoC repositories and NVD exploit links, returning ranked results.

Instructions

Discover public proof-of-concept (PoC) and exploit references for a CVE.

Aggregates the nomi-sec "PoC-in-GitHub" index (public GitHub repos tagged to the CVE, ranked by stars) and, by default, Exploit-DB / exploit-tagged references from the NVD record. Returns links and metadata only — use cve_fetch_poc_code to retrieve a specific repo's contents.

Intended for authorized defensive testing, detection engineering, and vulnerability triage.

Args:

  • cve_id (string): CVE identifier, e.g. "CVE-2021-44228".

  • include_nvd_exploits (boolean): Include NVD exploit references (default: true).

  • max_results (1-100, default 30): Cap on references returned.

  • response_format ('markdown'|'json', default 'markdown').

Returns (json): { cve_id, count, pocs: [ { source, name, url, description, stars, createdAt, updatedAt } ] }.

Examples:

  • "Find PoCs for Log4Shell" -> cve_id="CVE-2021-44228".

  • "Any exploits for CVE-2024-3400?" -> include_nvd_exploits=true.

Notes:

  • Returns an empty list (not an error) when no public PoCs are indexed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cve_idYesCVE identifier, e.g. 'CVE-2021-44228'.
max_resultsNoMaximum PoC references to return (1-100).
response_formatNoOutput format: 'markdown' (default, human-readable) or 'json' (full structured data).markdown
include_nvd_exploitsNoAlso include Exploit-DB / exploit-tagged references from the NVD record.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Even though annotations already include readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, the description adds substantial behavioral context: it aggregates two indexes, ranks GitHub repos by stars, returns only links and metadata, and notes that an empty list (not an error) is returned when no PoCs exist. This clarifies the operational behavior well beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every section earns its place: purpose, data sources, sibling differentiation, intended use, args, return shape, examples, and an edge-case note. It is well-structured with clear labels and front-loads the core purpose before diving into details. No redundant filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is complete for an agent to correctly call this tool: it defines all parameters, gives the JSON return shape, explains the empty-list edge case, provides examples, and clarifies why it differs from cve_fetch_poc_code. Given the rich annotations and full schema coverage, nothing necessary for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, which already documents all four parameters thoroughly. The description adds value with concrete natural-language examples mapping user requests to parameters, such as 'Find PoCs for Log4Shell' -> cve_id='CVE-2021-44228'. This helps the agent infer parameter values from user intent, but otherwise the parameter semantics are already well covered by the schema.

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 opens with a specific verb and resource: 'Discover public proof-of-concept (PoC) and exploit references for a CVE.' It goes beyond a simple restatement by naming the exact data sources (nomi-sec PoC-in-GitHub, NVD exploit references) and clearly distinguishes itself from cve_fetch_poc_code by noting it 'returns links and metadata only.' This makes the tool's scope unmistakable even before inspecting the schema.

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 tells the agent when to use a sibling instead: 'use cve_fetch_poc_code to retrieve a specific repo's contents.' It also frames the intended context ('authorized defensive testing, detection engineering, and vulnerability triage'), giving the agent clear guidance on when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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