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github_code_scanning_upload_sarif

Upload SARIF data to GitHub for code scanning analysis, enabling automated detection of security vulnerabilities and code quality issues.

Instructions

Upload an analysis as SARIF data

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYesowner
repoYesrepo
bodyNoRequest body (JSON object)

Implementation Reference

  • Handler function for github_code_scanning_upload_sarif that makes a POST request to /repos/{owner}/{repo}/code-scanning/sarifs with the provided body.
    handler: async (args: Record<string, any>) => {
      return githubRequest("POST", `/repos/${args.owner}/${args.repo}/code-scanning/sarifs`, args.body, undefined);
    },
  • Input schema defining the expected parameters: owner (string), repo (string), and optional body (record).
    inputSchema: z.object({
      owner: z.string().describe("owner"),
      repo: z.string().describe("repo"),
      body: z.record(z.string(), z.unknown()).optional().describe("Request body (JSON object)")
    }),
  • Tool definition registration within the codeScanningTools array, with name and description.
      name: "github_code_scanning_upload_sarif",
      description: "Upload an analysis as SARIF data",
      inputSchema: z.object({
        owner: z.string().describe("owner"),
        repo: z.string().describe("repo"),
        body: z.record(z.string(), z.unknown()).optional().describe("Request body (JSON object)")
      }),
      handler: async (args: Record<string, any>) => {
        return githubRequest("POST", `/repos/${args.owner}/${args.repo}/code-scanning/sarifs`, args.body, undefined);
      },
    },
  • The githubRequest helper function that all handlers use to make authenticated API calls to GitHub.
    export async function githubRequest<T>(
      method: string,
      path: string,
      body?: Record<string, unknown>,
      params?: Record<string, string | number | boolean | string[] | undefined>
    ): Promise<T> {
      const url = new URL(`${BASE_URL}${path}`);
    
      if (params) {
        for (const [key, value] of Object.entries(params)) {
          if (value === undefined || value === null || value === "") continue;
          if (Array.isArray(value)) {
            url.searchParams.set(key, value.join(","));
          } else {
            url.searchParams.set(key, String(value));
          }
        }
      }
    
      const headers: Record<string, string> = {
        Authorization: `Bearer ${getToken()}`,
        Accept: "application/vnd.github+json",
        "X-GitHub-Api-Version": "2022-11-28",
        "User-Agent": "github-mcp/1.0.0",
      };
    
      if (body) {
        headers["Content-Type"] = "application/json";
      }
    
      const res = await fetch(url.toString(), {
        method,
        headers,
        body: body ? JSON.stringify(body) : undefined,
      });
    
      if (!res.ok) {
        const text = await res.text().catch(() => "");
        let detail = text;
        try {
          const json = JSON.parse(text);
          detail = json.message || text;
          if (json.errors) detail += ` -- ${JSON.stringify(json.errors)}`;
        } catch {}
        throw new Error(`GitHub API error ${res.status}: ${detail}`);
      }
    
      if (res.status === 204) return {} as T;
    
      return res.json() as Promise<T>;
    }
Behavior2/5

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

No annotations are provided, so the description must carry behavioral transparency. It only states 'Upload an analysis as SARIF data' but omits side effects (e.g., replacing existing SARIF), required permissions, or rate limits. This is insufficient for an action-oriented tool.

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

Conciseness3/5

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

The description is a single sentence with 7 words, which is concise but lacks essential details. It is not wasteful, but could be improved by adding brief context without losing brevity.

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 no output schema and no annotations, the description should be more thorough. It does not explain the format of the body (SARIF JSON), whether it overwrites existing data, or any prerequisites. The tool is incomplete for a reliable agent invocation.

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 coverage is 100% (all parameters have descriptions), but the descriptions are trivial (just parameter names). The body parameter is an object without further explanation. The description adds no meaning beyond the schema, meeting the baseline for high coverage.

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 ('Upload') and the resource ('analysis as SARIF data'), indicating the tool's function. It distinguishes from siblings like get_sarif or create_variant_analysis by specifying the upload action and SARIF format.

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 on when to use this tool versus other code scanning tools (e.g., get_sarif, update_alert). The description does not provide context or alternatives, leaving the agent without decision support.

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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