Burpsuite MCP Server

by Cyreslab-AI

Overview Schema Related Servers Score Discussions

JavaScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: get_proxy_history retrieves captured traffic, get_scan_issues fetches vulnerability findings, get_scan_status checks scan progress, get_site_map provides site structure, and start_scan initiates new scans. The descriptions make it unambiguous which tool to use for each specific task.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with 'get_' or 'start_' prefixes followed by descriptive nouns (proxy_history, scan_issues, scan_status, site_map, scan). This uniform snake_case naming makes the tool set predictable and easy to understand.
Tool Count4/5
Five tools is reasonable for a BurpSuite security testing server, covering core functions like traffic capture, scanning, and results retrieval. While slightly lean, it provides essential operations without being overwhelming. A few additional tools for scan configuration or issue management could enhance completeness but aren't critical.
Completeness3/5
The tools cover basic scanning workflow (start, check status, get results) and proxy history, but lack operations for managing scans (e.g., pause, stop, configure) or interacting with issues (e.g., export, filter, annotate). This creates minor gaps that agents might need to work around, though core functionality is present.
Average 2.9/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
Tools from this server were used 40 times in the last 30 days.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on permissions needed, rate limits, whether it returns real-time or historical data, or the format of the returned traffic. For a tool that retrieves potentially sensitive proxy data, this is a significant gap in transparency.
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 a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of retrieving proxy traffic (which could involve large datasets or sensitive information), no annotations, and no output schema, the description is incomplete. It doesn't explain what the returned data looks like, any limitations, or how it integrates with the sibling tools, leaving gaps for an AI agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear descriptions for all four parameters (host, limit, method, status_code). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 without compensating for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('HTTP/HTTPS traffic captured by Burp Proxy'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_site_map' or 'get_scan_issues', which might also retrieve related data, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 versus alternatives. It doesn't mention any prerequisites, context for filtering traffic, or how it differs from siblings like 'get_site_map' (which might retrieve site structure) or 'get_scan_issues' (which might retrieve security findings).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states what the tool does without behavioral details. It lacks information on permissions, rate limits, pagination, or what happens if the scan_id is invalid, which is critical for a tool accessing vulnerability data.
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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of vulnerability scanning, lack of annotations, and no output schema, the description is insufficient. It doesn't explain return values, error handling, or behavioral constraints, leaving gaps that could hinder correct tool invocation by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'vulnerability issues' and 'scan', which aligns with the 'scan_id' parameter, but adds no meaning beyond the schema's 100% coverage. Since the schema fully describes both parameters, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('vulnerability issues found in a scan'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_scan_status' or 'get_proxy_history', which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't clarify if this should be used after 'start_scan' or alongside 'get_scan_status', leaving the agent without context for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a status check, which implies a read-only operation, but doesn't specify what the status includes (e.g., progress percentage, completion state, errors), whether it's real-time or cached, or any rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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 a single, clear sentence with zero wasted words. It's front-loaded with the core purpose and efficiently communicates the essential action without unnecessary elaboration, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a scan status tool (which likely involves dynamic state), no annotations, and no output schema, the description is insufficient. It doesn't explain what information is returned (e.g., progress, errors, duration), how to interpret status values, or potential edge cases. For a tool that agents will rely on to monitor operations, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'scan_id' documented as 'ID of the scan to check'. The description adds no additional meaning beyond this, such as format examples or where to obtain the ID. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check') and target resource ('status of a running scan'), making the purpose immediately understandable. It doesn't distinguish from siblings like 'get_scan_issues' or 'get_proxy_history', which would require more specific scope information, but it's unambiguous about what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 versus alternatives. It doesn't mention prerequisites (e.g., that a scan must be started first using 'start_scan'), nor does it differentiate from siblings like 'get_scan_issues' (which might return detailed problems) or 'get_proxy_history' (which might track proxy usage). Usage context is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Start a new vulnerability scan') but lacks details on execution traits, such as whether it's asynchronous, requires authentication, has rate limits, or what happens upon invocation (e.g., scan initiation vs. immediate results). This is inadequate for a mutation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of starting a vulnerability scan (a mutation operation with potential side effects), no annotations, and no output schema, the description is incomplete. It fails to address key contextual aspects like what the tool returns (e.g., a scan ID), error conditions, or behavioral implications, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both parameters (scan_type with enum values and target with examples). The description adds no additional parameter semantics beyond what the schema provides, such as explaining scan_type differences or target format nuances, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Start a new vulnerability scan') and the target ('on a target URL'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_scan_status' or 'get_scan_issues', which are related but not direct alternatives for initiating scans.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a target URL, or clarify its role relative to sibling tools like 'get_can_status' for monitoring scans. This leaves the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'site structure discovered during scanning and browsing,' implying a read-only operation, but doesn't specify if this is real-time data, cached results, or requires specific permissions. It also lacks details on output format, pagination, or error handling, which are critical for a tool with parameters like 'limit' and filtering options.
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 a single, efficient sentence: 'Get the site structure discovered during scanning and browsing.' It is front-loaded with the core purpose, uses clear language, and avoids unnecessary words. Every part of the sentence contributes directly to understanding the tool's function, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters with full schema coverage but no annotations or output schema, the description is minimally adequate. It covers the basic purpose but lacks context on behavioral aspects like data freshness, permissions, or output format. For a scanning-related tool that likely interacts with dynamic data, more details on how it integrates with siblings (e.g., after 'start_scan') would improve completeness, but it meets the minimum viable threshold.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for 'host' (filter by host), 'limit' (maximum items), and 'with_parameters' (only show URLs with parameters). The description doesn't add any meaning beyond this, as it doesn't explain how these parameters affect the 'site structure' retrieval or provide usage examples. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 the site structure discovered during scanning and browsing.' It specifies the verb ('Get') and resource ('site structure'), and distinguishes it from siblings like 'get_proxy_history' or 'get_scan_issues' by focusing on site structure rather than proxy logs or issues. However, it doesn't explicitly differentiate from 'get_scan_status' in terms of what 'site structure' entails versus 'status,' leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 versus alternatives. It doesn't mention any prerequisites, such as needing a scan to have been performed first, or compare it to siblings like 'get_scan_status' for status updates or 'start_scan' for initiating scans. Without such context, users might struggle to choose the right tool in this scanning-related set.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![burpsuite-mcp-server MCP server](https://glama.ai/mcp/servers/Cyreslab-AI/burpsuite-mcp-server/badges/card.svg)](https://glama.ai/mcp/servers/Cyreslab-AI/burpsuite-mcp-server)

Score Badge

Copy to your README.md:

[![burpsuite-mcp-server MCP server](https://glama.ai/mcp/servers/Cyreslab-AI/burpsuite-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/Cyreslab-AI/burpsuite-mcp-server)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Cyreslab-AI/burpsuite-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server