Skip to main content
Glama
offensive360

Offensive360 MCP Server

Official
by offensive360

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.1

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one initiates a scan and another checks its queue status. There is no overlap or ambiguity in their functions.

    Naming Consistency5/5

    Both tools follow the same 'o360_scan_' prefix followed by a noun, creating a consistent and predictable naming pattern.

    Tool Count3/5

    With only two tools, the set feels thin. The scope is narrowly focused on scanning and status, but the count is at the borderline of being too minimal.

    Completeness2/5

    The set covers initiating a scan and checking status, but lacks operations like retrieving results for finished scans, cancelling scans, or listing past scans. This creates a significant gap for users who need to manage scans over time.

  • Average 4.2/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 5 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • 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

  • Behavior3/5

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

    With no annotations, the description carries the behavioral transparency burden. It discloses the upload, waiting, and returning of findings, plus typical duration, which gives a good sense of the operation. It does not mention potential side effects like data being sent to Offensive360 cloud or what happens on timeout, but the main behavior is transparent.

    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?

    Three sentences, front-loaded with the primary action, and each sentence adds value: what it does, how it works, and expected duration. There is no redundancy or irrelevant detail.

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

    Completeness4/5

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

    The description covers the tool's purpose, process, output format, and timing, which is sufficient for a scanning tool. Given the schema fully documents parameters and the description explains the workflow, it is quite complete. It could optionally mention the sibling tool for status checks, but that's not essential.

    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?

    All four parameters are already described in the schema (path, exclude, project_name, timeout_seconds), so the description doesn't need to add much. The description itself does not elaborate on parameter formats or default behavior beyond what the schema provides, so it meets the baseline without adding extra value.

    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 clearly states the tool runs an Offensive360 SAST scan on a local directory, listing capabilities (60+ languages, taint/data-flow analysis) and expected output (findings with file/line, severity, remediation). It distinguishes from sibling o360_scan_status by describing the scan-trigger behavior rather than status checking.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description gives context on what the tool does (uploads zip, waits, returns findings) and typical duration, which implies it's for running a full scan. However, it does not explicitly mention when to use this tool versus o360_scan_status, nor any prerequisites or exclusions for using this tool.

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

  • Behavior4/5

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

    With no annotations provided, the description carries the full burden and does well by disclosing the exact return contract (0, positive number, -1) and what -1 represents (finished or unknown). While it doesn't mention error cases or side effects, the read-only nature of a status check is implied and the key behaviors are transparent.

    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 two concise sentences, front-loaded with the core action, and contains zero redundant information. Every word contributes to understanding the tool's function and behavior.

    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?

    For a simple one-parameter status tool with no output schema, the description is fully complete: it defines the input, the workflow context, and the exact meaning of all possible return values. There are no gaps in what the agent needs to invoke and interpret this tool correctly.

    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?

    The schema already describes project_name, but the description adds that it is the name 'used when the scan was started' via o360_scan_path, linking the parameter to its origin and adding practical context beyond 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 states a specific verb ('Check'), resource ('queue position of an Offensive360 scan'), and scope, and it explicitly references the sibling tool o360_scan_path, distinguishing this as the status-check follow-up. It also clearly explains the meaning of return values, making the purpose unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description implicitly guides usage by stating scans are 'started with o360_scan_path', indicating this tool should be used afterward to check status. It does not explicitly state exclusions or alternatives, but for a single-sibling workflow the context is clear.

    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

mcp-server MCP server

Copy to your README.md:

Score Badge

mcp-server MCP server

Copy to your README.md:

Latest Blog Posts

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/offensive360/mcp-server'

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