virustotal-mcp-server
Provides comprehensive security analysis using the VirusTotal API, including threat analysis on URLs, files, IP addresses, and domains with automatic relationship fetching for detailed security context.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@virustotal-mcp-serveranalyze URL https://example.com"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
VirusTotal MCP Server
A Model Context Protocol (MCP) server for comprehensive security analysis using the VirusTotal API. Built with FastMCP and Python, this server provides AI assistants like Claude with powerful malware detection and threat intelligence capabilities.
Overview
This MCP server integrates VirusTotal's extensive security database, allowing AI assistants to perform comprehensive security analysis on URLs, files, IP addresses, and domains. The server automatically fetches relationship data to provide complete security context in a single request.
Related MCP server: ThreatMCP
Features
Comprehensive Security Analysis: Complete threat analysis with automatic relationship fetching
URL Analysis: Security reports with contacted domains, downloaded files, and threat actors
File Analysis: Detailed file hash analysis including behaviors, dropped files, and network connections
IP Analysis: Geolocation, reputation data, and historical information
Domain Analysis: DNS records, WHOIS data, SSL certificates, and subdomains
Detailed Relationship Queries: Paginated access to specific relationship types for deep investigation
Rate Limit Aware: Respects VirusTotal API limitations
Multiple Transport Support: SSE and STDIO transports for different integration needs
Quick Start
Prerequisites
Python 3.8+ or Docker
uv package manager (for local development)
VirusTotal API key (Get one here)
Installation
Option 1: Docker (Recommended)
Clone and setup:
git clone https://github.com/barvhaim/virustotal-mcp-server.git cd virustotal-mcp-serverConfigure API key:
echo "VIRUSTOTAL_API_KEY=your_api_key_here" > .envRun with Docker Compose:
docker-compose up -dOr run with Docker directly:
docker build -t virustotal-mcp . docker run -d --name virustotal-mcp -p 8000:8000 --env-file .env virustotal-mcp
Option 2: Local Development
Clone and setup:
git clone https://github.com/barvhaim/virustotal-mcp-server.git cd virustotal-mcp-server uv syncConfigure API key:
echo "VIRUSTOTAL_API_KEY=your_api_key_here" > .envRun the server:
# SSE transport (web-friendly) uv run main.py # STDIO transport (for Claude Desktop) MCP_TRANSPORT=stdio uv run main.py
Tools Available
Report Tools (with Automatic Relationship Fetching)
1. URL Report Tool
Name:
get_url_reportDescription: Get comprehensive URL analysis including security scan results and key relationships
Parameters:
url(required): The URL to analyze
Auto-fetched relationships: communicating files, contacted domains/IPs, downloaded files, redirects, threat actors
2. File Report Tool
Name:
get_file_reportDescription: Get comprehensive file analysis using hash (MD5/SHA-1/SHA-256)
Parameters:
hash(required): File hash to analyze
Auto-fetched relationships: behaviors, dropped files, contacted domains/IPs, embedded URLs, threat actors
3. IP Report Tool
Name:
get_ip_reportDescription: Get comprehensive IP address analysis including geolocation and reputation
Parameters:
ip(required): IP address to analyze
Auto-fetched relationships: communicating files, historical SSL certificates, resolutions, threat actors
4. Domain Report Tool
Name:
get_domain_reportDescription: Get comprehensive domain analysis including DNS and WHOIS data
Parameters:
domain(required): Domain name to analyzerelationships(optional): Specific relationships to include
Auto-fetched relationships: subdomains, historical SSL certificates, resolutions, threat actors
Relationship Tools (for Detailed Analysis)
1. URL Relationship Tool
Name:
get_url_relationshipDescription: Query specific relationship types for URLs with pagination
Parameters:
url(required): The URL to analyzerelationship(required): Relationship type (analyses, communicating_files, contacted_domains, etc.)limit(optional, 1-40, default: 10): Number of resultscursor(optional): Pagination cursor
2. File Relationship Tool
Name:
get_file_relationshipDescription: Query specific relationship types for files with pagination
Parameters:
hash(required): File hashrelationship(required): Relationship type (behaviours, dropped_files, contacted_domains, etc.)limit(optional, 1-40, default: 10): Number of resultscursor(optional): Pagination cursor
3. IP Relationship Tool
Name:
get_ip_relationshipDescription: Query specific relationship types for IPs with pagination
Parameters:
ip(required): IP addressrelationship(required): Relationship type (communicating_files, resolutions, etc.)limit(optional, 1-40, default: 10): Number of resultscursor(optional): Pagination cursor
4. Domain Relationship Tool
Name:
get_domain_relationshipDescription: Query specific relationship types for domains with pagination
Parameters:
domain(required): Domain namerelationship(required): Relationship type (subdomains, historical_ssl_certificates, etc.)limit(optional, 1-40, default: 10): Number of resultscursor(optional): Pagination cursor
Claude Desktop Integration
To connect this server to Claude Desktop, add the following to your claude_desktop_config.json:
Configuration file locations:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonLinux:
~/.config/claude/claude_desktop_config.jsonWindows:
%APPDATA%\\Claude\\claude_desktop_config.json
{
"mcpServers": {
"virustotal": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/virustotal-mcp-server",
"run",
"main.py"
],
"env": {
"VIRUSTOTAL_API_KEY": "your_api_key_here",
"MCP_TRANSPORT": "stdio"
}
}
}
}Resources
FastMCP Documentation: github.com/jlowin/fastmcp
MCP Specification: modelcontextprotocol.io
VirusTotal API: developers.virustotal.com
uv Package Manager: astral.sh/uv
Claude Desktop: claude.ai
Version History
v1.0.0: Initial release with comprehensive VirusTotal integration
8 security analysis tools
Automatic relationship fetching
SSE and STDIO transport support
Rate limiting awareness
Complete error handling
Available Tools
8 toolsget_domain_relationshipA
Query a specific relationship type for a domain with pagination support.
Args: domain: Domain name to analyze relationship: Type of relationship to query limit: Maximum number of related objects to retrieve (1-40) cursor: Continuation cursor for pagination
Returns: str: Formatted relationship data
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| cursor | No | ||
| domain | Yes | ||
| relationship | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses pagination support and the return type (formatted string), but does not mention error conditions, rate limits, or explicitly confirm read-only behavior. While 'query' implies a read operation, this is not explicit.
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?
The description is front-loaded with a clear purpose sentence, followed by a structured argument list and a returns line. Every line adds information and there is no redundancy, making it efficient and well-organized.
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?
The output schema exists, so return value explanation is not strictly necessary, but the description still provides it. For a 4-parameter read-only tool with no annotations, the description is mostly complete, though it lacks guidance on valid relationship types or error handling, which would make it fully self-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 description coverage is 0%, and the description fully compensates by explaining each parameter: domain, relationship, limit with an explicit range (1-40), and cursor as a continuation token. This adds significant meaning beyond the bare type definitions in 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?
The description uses the specific verb 'Query' with the resource 'a specific relationship type for a domain' and adds 'with pagination support,' clearly defining scope. It distinguishes from sibling report tools (e.g., get_domain_report) by focusing on relationships rather than full reports, and from other relationship tools by the domain scope.
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?
The description states the tool's function and mentions pagination, but it does not explicitly state when to prefer this tool over get_domain_report or the other relationship tools (get_url_relationship, get_file_relationship, get_ip_relationship). No exclusions or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_domain_reportA
Get a comprehensive domain analysis report.
Args: domain: Domain name to analyze relationships: Optional list of specific relationships to include
Returns: str: Formatted analysis report with detection summary and relationships
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | ||
| relationships | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the return type (a string with detection summary and relationships) and the effect of the relationships parameter. However, it does not explicitly state read-only behavior, error conditions, or any side effects, which is a minor gap for a report tool.
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?
The description is succinct and well-structured with Args and Returns sections. Every sentence adds useful content without redundancy, and the main purpose 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?
For a tool with 2 parameters and no annotations, the description covers the purpose, parameters, and return value sufficiently. It does not describe usage scenarios or explicit alternatives, but the context signals (sibling names) and clear parameter hints make this fairly complete.
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 0%, so the description is the sole source of parameter meaning. It explains 'domain' as the domain name to analyze and 'relationships' as an optional list of specific relationships to include, adding value beyond the raw schema. It could provide more detail on what relationships are valid, but it compensates adequately.
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's purpose: 'Get a comprehensive domain analysis report.' The verb 'Get' and resource 'domain analysis report' are specific, and it distinguishes from sibling tools by focusing on domains (vs URL, file, IP) and being a report (vs relationship-specific tools).
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?
The description does not explicitly name alternatives or state when not to use it, but the context is clear: use for a full domain analysis report. The optional 'relationships' parameter implies that for a single relationship lookup, get_domain_relationship might be sufficient, but this is not stated explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_file_relationshipA
Query a specific relationship type for a file with pagination support.
Args: file_hash: MD5, SHA-1 or SHA-256 hash of the file relationship: Type of relationship to query limit: Maximum number of related objects to retrieve (1-40) cursor: Continuation cursor for pagination
Returns: str: Formatted relationship data
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| cursor | No | ||
| file_hash | Yes | ||
| relationship | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses pagination support and the return type (formatted string), but omits potential error behaviors, authentication requirements, or any side effects. For a query tool, this is reasonable but incomplete.
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?
The description is efficient and well-organized: a one-sentence summary followed by a clear Args list and Returns note. No redundant information, and the structure makes it easy to parse.
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?
The description covers the main operation, parameters, and pagination, but it does not enumerate valid relationship types or describe error conditions. Given no annotations and a minimal output schema, this leaves gaps that an agent would need to infer.
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?
The 'Args' section thoroughly explains all four parameters, including accepted hash formats (MD5, SHA-1, SHA-256), the limit range (1-40), and cursor meaning for pagination. This compensates for the 0% schema description coverage and adds significant value.
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 opens with 'Query a specific relationship type for a file with pagination support,' providing a specific verb (query) and resource (file relationship). It clearly distinguishes from siblings like get_url_relationship and get_file_report.
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?
The description states the tool's function but does not provide explicit guidance on when to use this tool versus alternatives, such as get_url_relationship or get_domain_relationship. Usage is implied by the file-specific focus, but no contextual or exclusionary guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_file_reportA
Get a comprehensive file analysis report using its hash.
Args: file_hash: MD5, SHA-1 or SHA-256 hash of the file
Returns: str: Formatted analysis report with detection summary and relationships
| Name | Required | Description | Default |
|---|---|---|---|
| file_hash | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return type (str) and content ('formatted analysis report with detection summary and relationships'), which is helpful. However, it does not cover failure modes, what happens with an unknown hash, or whether external lookups are involved. This is basic transparency, not rich.
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?
The description is concise and well-structured: a one-sentence purpose followed by explicit Args and Returns sections. Every line earns its place with no redundancy or filler.
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?
For a single-parameter tool with an output schema, the description covers purpose, parameter format, and return content. It does not elaborate on error cases or usage scenarios, but the tool is simple enough that this is acceptable. The existence of an output schema reduces the need to describe return structure in detail.
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?
The input schema only says 'File Hash' with 0% coverage, so the description's clarification that it accepts MD5, SHA-1, or SHA-256 is essential and adds meaningful semantics. It could include examples or mention accepted formats, but for a single required parameter, this is adequate and more than the schema provides.
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 uses a specific verb ('Get') and resource ('comprehensive file analysis report') with the method ('using its hash'). It distinguishes itself from sibling tools like get_url_report and get_ip_report by specifying 'file' and 'hash', making the purpose unmistakable.
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?
The description clearly implies when to use the tool: when you have a file hash and want a detailed report. It does not explicitly mention alternatives or exclusions, but the sibling tool names and the 'using its hash' wording provide enough contextual guidance. Lacks explicit 'when not to use', so not a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_ip_relationshipA
Query a specific relationship type for an IP address with pagination support.
Args: ip: IP address to analyze relationship: Type of relationship to query limit: Maximum number of related objects to retrieve (1-40) cursor: Continuation cursor for pagination
Returns: str: Formatted relationship data
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | ||
| limit | No | ||
| cursor | No | ||
| relationship | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It mentions pagination support and a return type, which adds some context, but does not explicitly state read-only behavior, rate limits, or error handling. The query verb implies non-mutating, but it is not explicit.
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?
The description is tightly written: one opening sentence, a clean Args list, and a Returns line. No redundant or filler content; every line contributes to understanding.
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?
For a 4-parameter tool with no annotations and no detailed output schema, the description provides basic parameter and return information but lacks completeness. The return type ('Formatted relationship data') is vague, and valid relationship types or input constraints are not documented, leaving gaps 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?
The description provides direct explanations for all parameters (ip, relationship, limit, cursor) beyond the schema, including the limit range (1-40) and cursor purpose. Schema coverage is 0%, so this fully compensates and adds meaningful semantics.
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 uses a specific verb 'Query' with resource 'IP address' and clearly specifies 'relationship type', distinguishing it from sibling tools like get_ip_report and other relationship tools. The name itself aligns with the purpose.
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?
The description implies when to use the tool (when needing relationship data for an IP) but does not explicitly state alternatives or exclusions. It lacks guidance on when to choose this over get_ip_report or other relationship tools, leaving usage context implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_ip_reportA
Get a comprehensive IP address analysis report.
Args: ip: IP address to analyze
Returns: str: Formatted analysis report with detection summary and relationships
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It mentions the return format ('Formatted analysis report with detection summary and relationships') but fails to disclose other behavioral traits such as read-only safety, rate limits, or any external calls. This is a significant gap for a tool with zero annotation coverage.
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?
The description is concise and well-structured with a single-sentence overview, followed by Args and Returns sections. Every part adds value, avoiding fluff while providing the necessary parameter and return 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?
For a tool with one parameter and a string return, the description is mostly complete: it explains the parameter, the return type, and the report's content. However, it omits behavioral context (e.g., no mention of prerequisites or side effects) and does not address alternatives, despite the presence of sibling tools. The lower complexity prevents a lower score, but the gaps keep it from a 5.
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?
The schema provides no description for the 'ip' parameter (coverage 0%), but the description compensates with 'ip: IP address to analyze', adding clear meaning. It explains the purpose of the parameter without needing examples or format details, which is adequate for a single string parameter.
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 uses a specific verb 'Get' with a clear resource 'IP address analysis report'. It distinguishes from sibling tools by focusing on IPs and the 'report' aspect rather than 'relationship', making the tool's purpose unambiguous.
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?
The description implies usage: when you need a report for an IP, use this tool. However, it lacks explicit guidance on when not to use it or alternatives like get_ip_relationship, which also covers relationships. No exclusions or comparison with sibling tools are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_url_relationshipA
Query a specific relationship type for a URL with pagination support.
Args: url: The URL to get relationships for relationship: Type of relationship to query limit: Maximum number of related objects to retrieve (1-40) cursor: Continuation cursor for pagination
Returns: str: Formatted relationship data
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| limit | No | ||
| cursor | No | ||
| relationship | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It discloses that the operation is a read-only query ('Query'), supports pagination via limit/cursor, and returns formatted data. However, it does not describe error behavior, authentication requirements, rate limits, or whether the URL must be exact. While the 'Query' verb implies non-destructive behavior, the description could be richer for an unannotated tool.
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?
The description is efficiently structured as a docstring with a one-sentence summary followed by Args and Returns sections. It is front-loaded with the core purpose, every sentence provides necessary information, and there is no fluff or repetition. The formatting is clean and easy to parse.
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?
The description covers the main parameters and return type, and an output schema exists so the return format is not the description's responsibility. However, it omits crucial contextual details such as valid relationship types (e.g., which ones are supported), URL format expectations, and error handling. Given there are no annotations and relatively complex behavior (pagination), the description is only partially complete for an agent to use the tool reliably.
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?
The schema has no descriptions (0% coverage), so the description must compensate. It provides one-line descriptions for each parameter, and notably adds useful constraints for 'limit' (maximum 1-40) and 'cursor' (continuation cursor). For 'url' and 'relationship,' the descriptions ('The URL to get relationships for' and 'Type of relationship to query') are close to restating the parameter names, and no allowed values or format details are given. This partial enrichment warrants a mid-score.
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 opens with 'Query a specific relationship type for a URL with pagination support,' which clearly identifies the action (query), the resource (URL), and the specific aspect (relationship type). It distinguishes this tool from siblings like get_url_report (report vs relationship) and other relationship tools (file/ip/domain) by explicitly stating 'for a URL.'
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?
The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention that this should be used specifically for relationships (not reports) or that other relationship tools cover different resource types. No exclusions or alternative tool names are mentioned, so an agent is left to infer from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_url_reportA
Get comprehensive URL analysis report with security results and relationships.
Args: url: The URL to analyze
Returns: str: Formatted analysis report with detection summary and relationships
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the burden. It implies a read-only operation via 'Get' and states what returns (formatted analysis report). However, it doesn't disclose potential side effects, external dependencies, or whether the report is cached or real-time, which is somewhat expected for a report tool.
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?
The description is concise and well-structured. It leads with a one-sentence summary of the tool's purpose, followed by clearly labeled Args and Returns sections. There is no redundant or extraneous text.
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 tool's low complexity (one parameter, no nested objects) and the presence of an output schema, the description provides sufficient context for an agent to invoke it correctly. It doesn't mention sibling distinctions, but that is not essential for completeness in this simple case.
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?
The schema for the single parameter 'url' only includes its type and title. The description compensates by explaining 'url: The URL to analyze,' which adds semantic meaning beyond the schema. Since schema coverage is 0%, this explanation is valuable and sufficient for a single self-explanatory parameter.
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 'Get comprehensive URL analysis report' with a specific resource (URL) and verb (Get). It is obvious what the tool does, but it doesn't explicitly distinguish itself from sibling tools like get_domain_report or get_url_relationship.
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?
The description provides no guidance on when to use this tool compared to alternatives (e.g., get_domain_report for domains). It does not mention any exclusions, prerequisites, or contextual triggers for selecting this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
8 tool updates
v0.1.0- First observed
get_domain_relationship - First observed
get_domain_report - First observed
get_file_relationship - First observed
get_file_report - First observed
get_ip_relationship - First observed
get_ip_report - First observed
get_url_relationship - First observed
get_url_report
TDQS
Scored across 8 tools
Each tool targets a distinct resource type (URL, file, IP, domain) combined with a distinct action (report vs relationship). There is no overlap or ambiguity between tools; an agent can easily select the right one based on resource and intent.
All tool names follow a clear and consistent verb_noun pattern: get_<resource>_report and get_<resource>_relationship. The naming is uniform, predictable, and uses snake_case throughout.
With exactly 8 tools, the set is well-scoped for the domain. Each tool covers a core API operation for one of four resource types, and no redundant or unnecessary tools exist.
The tool surface covers report retrieval and relationship queries for all major VirusTotal resources (URL, file, IP, domain). It lacks submission/scanning tools, but for a read-focused MCP server the coverage is quite complete; only a minor gap.
Maintenance
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