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GitHub MCP Server Plus

create_branch

Create a new branch in a GitHub repository by specifying owner, repository name, and branch name, optionally from a source branch.

Instructions

Create a new branch in a GitHub repository

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYesRepository owner (username or organization)
repoYesRepository name
branchYesName for the new branch
from_branchNoOptional: source branch to create from (defaults to the repository's default branch)

Implementation Reference

  • Dispatcher handler for the "create_branch" tool: parses input arguments using the schema and calls the branches.createBranchFromRef function to execute the tool logic.
    case "create_branch": {
      const args = branches.CreateBranchSchema.parse(request.params.arguments);
      const branch = await branches.createBranchFromRef(
        args.owner,
        args.repo,
        args.branch,
        args.from_branch
      );
      return {
        content: [{ type: "text", text: JSON.stringify(branch, null, 2) }],
      };
    }
  • Primary handler function implementing the create_branch tool logic: determines the SHA of the source branch (or default), then calls createBranch to perform the GitHub API call.
    export async function createBranchFromRef(
      owner: string,
      repo: string,
      newBranch: string,
      fromBranch?: string
    ): Promise<z.infer<typeof GitHubReferenceSchema>> {
      let sha: string;
      if (fromBranch) {
        sha = await getBranchSHA(owner, repo, fromBranch);
      } else {
        sha = await getDefaultBranchSHA(owner, repo);
      }
    
      return createBranch(owner, repo, {
        ref: newBranch,
        sha,
      });
    }
  • Core helper function that executes the GitHub API POST request to create a new git reference (branch).
    export async function createBranch(
      owner: string,
      repo: string,
      options: CreateBranchOptions
    ): Promise<z.infer<typeof GitHubReferenceSchema>> {
      const fullRef = `refs/heads/${options.ref}`;
    
      const response = await githubRequest(
        `https://api.github.com/repos/${owner}/${repo}/git/refs`,
        {
          method: "POST",
          body: {
            ref: fullRef,
            sha: options.sha,
          },
        }
      );
    
      return GitHubReferenceSchema.parse(response);
    }
  • Zod schema defining the input parameters for the create_branch tool, used for validation in the handler and tool registration."},{
    export const CreateBranchSchema = z.object({
      owner: z.string().describe("Repository owner (username or organization)"),
      repo: z.string().describe("Repository name"),
      branch: z.string().describe("Name for the new branch"),
      from_branch: z.string().optional().describe("Optional: source branch to create from (defaults to the repository's default branch)"),
    });
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. While 'Create' implies a mutation, the description lacks details on permissions required, whether the operation is idempotent, error handling (e.g., if the branch already exists), or rate limits. 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'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 a GitHub branch creation tool (a mutation with potential side effects), no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like authentication needs, error cases, or return values, leaving significant gaps for an AI agent to use it correctly.

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 adds no parameter-specific information beyond what's in the input schema, which has 100% coverage with clear descriptions for all four parameters. This meets the baseline of 3, as the schema fully documents the parameters, but the description doesn't enhance understanding with additional context or examples.

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 ('Create') and resource ('new branch in a GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'create_repository' or 'create_pull_request' beyond the obvious resource difference, missing explicit sibling distinction.

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., needing repository access), when not to use it (e.g., for existing branches), or how it relates to siblings like 'fork_repository' or 'create_pull_request' for branch-related workflows.

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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