osv-advisory-mcp-server
Server Details
Query OSV.dev for package vulnerabilities and batch-audit dependency lists via MCP.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.8/5 across 4 of 4 tools scored.
Each tool has a clearly distinct purpose: fetching full advisories, listing ecosystems, querying single packages, and batch queries. There is no overlap or ambiguity.
All tools follow a consistent 'osv_verb_noun' pattern (get_vulnerability, list_ecosystems, query, query_batch). The naming is predictable and uniform.
Four tools is well-scoped for the OSV advisory domain, covering ecosystem discovery, single and batch vulnerability queries, and detailed advisory retrieval without bloat.
The tool set covers all necessary operations for a read-only vulnerability database: listing supported ecosystems, querying individual packages, batch queries for audits, and retrieving full advisory records. No obvious gaps.
Available Tools
4 toolsosv_get_vulnerabilityOsv Get VulnerabilityARead-onlyIdempotentInspect
Fetch the full advisory record for an OSV vulnerability ID. Returns the complete record: summary, full details text, CVE aliases, all affected packages and version ranges, fix versions, CVSS severity vectors, CWE weakness IDs, and references. Use when osv_query or osv_query_batch returns a vuln ID and you need the full advisory context — eligibility criteria, scope of affected packages, or remediation guidance.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | OSV vulnerability ID. Accepts any prefix: "GHSA-" (GitHub), "PYSEC-" (Python), "RUSTSEC-" (Rust), "GO-" (Go), "DSA-"/"DLA-" (Debian), "CVE-" (fallback direct lookups). Example: "GHSA-29mw-wpgm-hmr9". |
Output Schema
| Name | Required | Description |
|---|---|---|
| id | Yes | OSV vulnerability ID. |
| cweIds | Yes | CWE weakness classifications (e.g. ["CWE-79"]). Present on GitHub Advisory Database records; empty otherwise. |
| aliases | Yes | Alternative IDs — usually CVE IDs. Accepted by nvd_get_cve on nist-nvd-mcp-server for CVSS base score, EPSS exploitation probability, and CISA KEV status. |
| details | Yes | Full advisory text, typically in Markdown. May include proof-of-concept, reproduction steps, or remediation guidance. |
| summary | Yes | One-line advisory description. |
| affected | Yes | All affected packages and their version ranges. An advisory may span multiple packages or ecosystems. |
| modified | Yes | ISO 8601 timestamp of last modification. |
| severity | Yes | CVSS severity entries. Empty for unscored advisories. |
| published | Yes | ISO 8601 timestamp when published. |
| references | Yes | Advisory references — NVD links, patches, vendor advisories, PoC reports. |
| schemaVersion | Yes | OSV schema version this record conforms to (e.g. "1.7.3"). |
| severityLabel | Yes | Human-readable severity label ("LOW", "MODERATE", "HIGH", "CRITICAL"). Present on GHSA-sourced records; null when not available. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the description only adds context about acceptable ID prefixes. It does not disclose any additional behavioral traits like rate limits, but given annotation coverage, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The first sentence states purpose and contents; the second provides context. Information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description need not explain return values. It covers purpose, usage, parameter details, and context, making it fully actionable for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, yet the description adds significant value by listing accepted ID prefixes (GHSA-, PYSEC-, etc.) and providing an example. This goes beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches the full advisory record for an OSV vulnerability ID, specifying the action and resource. It also distinguishes from sibling tools by referencing osv_query and osv_query_batch.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use when osv_query or osv_query_batch returns a vuln ID and you need the full advisory context.' This guidelines direct the agent from related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
osv_list_ecosystemsOsv List EcosystemsARead-onlyIdempotentInspect
Return the list of supported ecosystem identifier strings for use with osv_query and osv_query_batch. Ecosystem strings are case-sensitive exact matches — passing "pypi" instead of "PyPI" returns an error from the API. Use this tool to discover valid ecosystem strings before querying, or to verify an ecosystem identifier from a lockfile format. The list is static (maintained from the OSV schema spec) and may occasionally lag newly added ecosystems.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| note | Yes | Advisory note about list currency and canonical source. |
| ecosystems | Yes | Supported ecosystem identifier strings. These are case-sensitive exact matches required by the ecosystem parameter of osv_query and osv_query_batch. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and idempotentHint. Description adds valuable context about case-sensitivity leading to errors, static nature of the list, and potential lag. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two well-structured sentences that are front-loaded with the core purpose. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, an output schema exists, and annotations cover safety, the description provides sufficient context for usage, behavior, and constraints. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist in the schema, so baseline is 4. The description adds no parameter information because none are needed; schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns a list of supported ecosystem identifier strings for use with osv_query and osv_query_batch. It distinguishes itself from siblings by explaining its role as a discovery tool for valid ecosystem strings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: before querying to discover valid ecosystems or to verify identifiers. Notes that ecosystem strings are case-sensitive and may lag, and mentions sibling tools osv_query and osv_query_batch.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
osv_queryOsv QueryARead-onlyIdempotentInspect
Query known vulnerabilities for a single package version across any supported ecosystem. Returns all matching OSV advisories with severity (CVSS vectors), CVE aliases, affected version ranges, and first safe version. Use osv_list_ecosystems to validate the ecosystem string before querying — ecosystem strings are case-sensitive exact matches and an invalid value returns an error, not empty results.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Package name as it appears in the ecosystem (e.g. "express", "requests", "serde"). Case-sensitive. | |
| version | Yes | Package version to check (e.g. "4.17.1", "3.1.4", "1.0.0"). Must be an exact version string, not a range. | |
| ecosystem | Yes | Ecosystem identifier. Must be an exact match (case-sensitive). Use osv_list_ecosystems to see valid values. Examples: "npm", "PyPI", "crates.io", "Go", "Maven", "NuGet". |
Output Schema
| Name | Required | Description |
|---|---|---|
| vulns | Yes | Vulnerabilities matching this package version. Empty array means no known vulnerabilities. |
| queryMeta | Yes | Query parameters as submitted. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent behavior. The description adds details about return content (CVSS, CVE aliases, ranges, first safe version) and warns about ecosystem case-sensitivity and error behavior, going beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first clearly states purpose and output, second provides critical usage warning and alternative. No unnecessary words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description covers all essential aspects: purpose, parameter constraints, return contents, and a crucial usage caveat. It is complete for a single-query tool with good annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions. The description adds value by emphasizing ecosystem case-sensitivity and the need for exact match, plus the consequence of invalid ecosystem (error, not empty). This extra context justifies above the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool queries known vulnerabilities for a single package version across any ecosystem. It uses specific verb 'query' and resource 'vulnerabilities', and differentiates from siblings like osv_query_batch (batch) and osv_list_ecosystems (listing ecosystems).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use (single package version query) and when not to (invalid ecosystem returns error). It names the alternative tool osv_list_ecosystems for validation, providing clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
osv_query_batchOsv Query BatchARead-onlyIdempotentInspect
Query vulnerabilities for multiple packages in one call — the primary tool for dependency audits, SBOM scanning, and lockfile triage. Pass an array of {name, ecosystem, version} tuples (up to 1000). Each entry in the response corresponds positionally to the input. Each finding includes CVE aliases for chaining to nist-nvd-mcp-server for CVSS scoring. Invalid ecosystem strings are rejected before querying — call osv_list_ecosystems to validate.
| Name | Required | Description | Default |
|---|---|---|---|
| packages | Yes | Packages to audit. One entry per dependency. Positional: result[i] corresponds to packages[i]. |
Output Schema
| Name | Required | Description |
|---|---|---|
| results | Yes | Per-package results, positionally matching the input array. |
| summary | Yes | Aggregate statistics across the full batch. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint. Description adds crucial behaviors: positional correspondence, spill to DataCanvas for large result sets, early rejection of invalid ecosystems, and CVE aliases for chaining. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences efficiently convey purpose, behavior, constraints, and chaining. Front-loaded with purpose. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (batch query, spill mechanism, chaining, validation), the description covers all key aspects. Output schema exists for detailed structure, so description's coverage is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds valuable context: array limit of 1000, positional mapping, and canvas_id reuse for large results. This supplements rather than repeats the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states it queries vulnerabilities for multiple packages in one call, and positions it as the primary tool for dependency audits, SBOM scanning, and lockfile triage. This clearly differentiates from sibling tools like osv_query (singular) and osv_list_ecosystems.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage contexts (dependency audits, SBOM scanning) and mentions when to use osv_list_ecosystems for validation. However, it does not explicitly contrast with osv_query for single-package queries.
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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