This record as markdown: /tools/io-github-dave-london-git/bazel.md
What bazel does on Git
AI agents invoke bazel to trigger actions in Git. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why bazel is rated High
Bazel is a build system that can execute arbitrary code during builds and tests. The 'run' operation directly executes compiled binaries or scripts, and 'build' compiles and may execute build rules that can have arbitrary side effects. The 'clean' operation modifies the build artifact state.
From the tool's definition Tool offers 'build', 'test', 'run', 'clean', and 'fetch' operations for the Bazel build system. The 'run' and 'build' capabilities execute arbitrary code and external operations whose side effects depend on what the build configuration and scripts specify.
Attacks that exploit this kind of access
The rule that runs bazel safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Git, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For bazel, this is the rule to start with:
bazel stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Git, apply this rule, and every bazel call is checked against it from then on.
Questions about bazel
Bazel build system operations: build, test, query, info, run, clean, fetch. It is categorised as a Execute tool in the Git MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Git MCP server in PolicyLayer and add a rule for bazel: 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 Git. Nothing to install.
bazel is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the bazel 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 bazel. 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.
bazel is provided by the Git MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Git, and thousands of servers like it.
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