AI agents call getProjectBranchingModel to retrieve information from Bitbucket MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves project branching model configuration data without creating, modifying, deleting, or executing any operations. It is a straightforward query that returns existing information about how a project manages branches. No state changes occur, and there are no irreversible actions, code execution, or financial implications.
From the tool's definition Tool name 'getProjectBranchingModel' and description 'Get the branching model for a project' indicate a retrieval operation with no modification or side effects.
Documented attack patterns abuse exactly the kind of access getProjectBranchingModel gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Bitbucket MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for getProjectBranchingModel:
{
"version": "1",
"default": "deny",
"tools": {
"getProjectBranchingModel": {}
}
}getProjectBranchingModel is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get the branching model for a project. It is categorised as a Read tool in the Bitbucket MCP MCP Server, which means it retrieves data without modifying state.
Register the Bitbucket MCP server in PolicyLayer and add a rule for getProjectBranchingModel: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Bitbucket MCP. Nothing to install.
getProjectBranchingModel is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the getProjectBranchingModel rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for getProjectBranchingModel. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
getProjectBranchingModel is provided by the Bitbucket MCP server (matanyemini/bitbucket-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Bitbucket MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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49 Bitbucket MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.