Add a local code repository to the documentation system. This tool indexes all files in the repository according to the specified configuration, processes them into searchable chunks, and stores them in the vector database for future searches.
AI agents use add_repository to create or update resources in RAG Documentation MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your RAG Documentation MCP Server environment.
This tool creates new indexed entries in a vector database and modifies the system's state by adding a repository to the documentation system. This is a reversible Write operation, not a Read (since it modifies state beyond simple queries), not Execute (no arbitrary code execution on the host), not Destructive (can be undone via remove_repository), and not Financial.
From the tool's definition The tool 'add_repository' performs actions that 'indexes all files in the repository' and 'stores them in the vector database' - these are data creation and modification operations that persist state in the system.
Risk signalsBulk/mass operation — affects multiple targets
Documented attack patterns abuse exactly the kind of access add_repository gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and RAG Documentation MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for add_repository:
{
"version": "1",
"default": "deny",
"tools": {
"add_repository": {
"limits": [
{
"counter": "add_repository_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_repository 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.
Free to start. No card required.
Add a local code repository to the documentation system. This tool indexes all files in the repository according to the specified configuration, processes them into searchable chunks, and stores them in the vector database for future searches. It is categorised as a Write tool in the RAG Documentation MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the RAG Documentation MCP Server MCP server in PolicyLayer and add a rule for add_repository: 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 RAG Documentation MCP Server. Nothing to install.
add_repository is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the add_repository 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 add_repository. 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.
add_repository is provided by the RAG Documentation MCP Server MCP server (rahulretnan/mcp-ragdocs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 14 RAG Documentation MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
14 RAG Documentation MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.