📊 Generate intelligent project navigation hints with word clouds, folder analysis, and architecture detection. Supports multiple output formats including markdown and HTML, with AI-powered analysis and configurable performance options. Accepts absolute paths or relative paths (when workspace can...
AI agents call local_project_hints to retrieve information from Ambiance MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and analyzes project structure information (hints, word clouds, folder analysis, architecture detection) and presents it in various formats (markdown, HTML). It performs semantic analysis and reporting on existing code without modifying any data or executing external operations.
From the tool's definition Tool description indicates 'Generate intelligent project navigation hints with word clouds, folder analysis, and architecture detection' - these are analytical, non-modifying operations that analyze and present information about a project structure.
Attacks that exploit this kind of access
📊 Generate intelligent project navigation hints with word clouds, folder analysis, and architecture detection. Supports multiple output formats including markdown and HTML, with AI-powered analysis and configurable performance options. Accepts absolute paths or relative paths (when workspace can be detected). It is categorised as a Read tool in the Ambiance MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Ambiance MCP Server MCP server in PolicyLayer and add a rule for local_project_hints: 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 Ambiance MCP Server. Nothing to install.
local_project_hints 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 local_project_hints 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 local_project_hints. 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.
local_project_hints is provided by the Ambiance MCP Server MCP server (sbarron/ambiancemcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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