rag_search

FBMCPF-264/315: local retrieval over this board

SERVERFeatureBoard SOURCEhttps://github.com/valentil/featureboard-mcp/releases/download/v0.7/featureboard.plugin

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/ai-featureboard-featureboard/rag-search.md

WHAT IT DOES

What rag_search does on FeatureBoard

AI agents call rag_search to retrieve information from FeatureBoard without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why rag_search is rated Low

This tool performs retrieval-augmented generation (RAG) search over local board data, querying and fetching information without modification, deletion, or execution of external operations. No side effects are described or implied. This is a standard Read category operation.

From the tool's definition Tool description states 'retrieval over this board' and tool name 'rag_search' indicates search/retrieval operation. Context shows this is a project board system where retrieval is a core read-only operation.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs rag_search safely

PolicyLayer is an MCP gateway: it sits between your AI agents and FeatureBoard, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For rag_search, this is the rule to start with:

rag_search Allowed

rag_search is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "rag_search": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect FeatureBoard, apply this rule, and every rag_search call is checked against it from then on.

FAQ

Questions about rag_search

What does the rag_search tool do? +

FBMCPF-264/315: local retrieval over this board. It is categorised as a Read tool in the FeatureBoard MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on rag_search? +

Register the FeatureBoard MCP server in PolicyLayer and add a rule for rag_search: 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 FeatureBoard. Nothing to install.

What risk level is rag_search? +

rag_search is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit rag_search? +

Yes. Add a rate_limit block to the rag_search 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 rag_search completely? +

Set action: deny in the PolicyLayer policy for rag_search. 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 rag_search? +

rag_search is provided by the FeatureBoard MCP server (https://github.com/valentil/featureboard-mcp/releases/download/v0.7/featureboard.plugin). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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