write_project_file · AI Development Pipeline MCP

WHAT IT DOES

What write_project_file does on AI Development Pipeline MCP

AI agents use write_project_file to create or update resources in AI Development Pipeline MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your AI Development Pipeline MCP environment.

WHY IT NEEDS A POLICY

Why write_project_file needs a policy

This tool creates or modifies files reversibly within a constrained workspace directory. It does not delete data (which would be Destructive) nor execute arbitrary code (Execute). The 'restricted to workspace directory' constraint mitigates but does not eliminate risk—an AI agent could still corrupt source code, configuration files, or dependencies, causing significant build failures or introducing vulnerabilities.

From the tool's definition Tool name is 'write_project_file' and description states 'Write to a local file in the VS Code workspace'. The verb 'Write' explicitly indicates data modification capability.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

write_project_file Rate-limited

write_project_file stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "write_project_file": {
      "limits": [
        {
          "counter": "write_project_file_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches AI Development Pipeline MCP, so you can run agents against it safely.

FAQ

Questions about write_project_file

What does the write_project_file tool do? +

Write to a local file in the VS Code workspace (restricted to workspace directory). It is categorised as a Write tool in the AI Development Pipeline MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on write_project_file? +

Register the AI Development Pipeline MCP server in PolicyLayer and add a rule for write_project_file: 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 AI Development Pipeline MCP. Nothing to install.

What risk level is write_project_file? +

write_project_file is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit write_project_file? +

Yes. Add a rate_limit block to the write_project_file 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.

How do I block write_project_file completely? +

Set action: deny in the PolicyLayer policy for write_project_file. 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.

What MCP server provides write_project_file? +

write_project_file is provided by the AI Development Pipeline MCP server (theburgerllc/ai-development-pipeline-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.