Search for code across repositories in a project
AI agents call search_code to retrieve information from Azure DevOps MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a search operation to retrieve and list code matching search criteria. It has no side effects—it does not execute code, modify repositories, delete content, or trigger any external operations. It is a read-only query operation similar to 'search' or 'get' operations.
From the tool's definition Tool name 'search_code' and description 'Search for code across repositories in a project' indicate a query/retrieval operation with no modification, creation, deletion, or execution of code.
Documented attack patterns abuse exactly the kind of access search_code gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Azure DevOps MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for search_code:
{
"version": "1",
"default": "deny",
"tools": {
"search_code": {}
}
}search_code is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search for code across repositories in a project. It is categorised as a Read tool in the Azure DevOps MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Azure DevOps MCP Server MCP server in PolicyLayer and add a rule for search_code: 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 Azure DevOps MCP Server. Nothing to install.
search_code 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 search_code 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 search_code. 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.
search_code is provided by the Azure DevOps MCP Server MCP server (tiberriver256/mcp-server-azure-devops). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 42 Azure DevOps MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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42 Azure DevOps MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.