Search notes by meaning rather than keywords. Embeds the query with the configured provider, scores every chunk in the persisted index by cosine similarity, ranks one result per note using the best chunk plus a small top-chunk focus signal, and returns the best chunk as the snippet source. Run
AI agents call search_semantic to retrieve information from Obsidian Mcp Pro without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
search_semantic performs semantic search over an Obsidian vault index using embeddings and cosine similarity ranking. It retrieves and ranks existing data (note chunks) but produces no side effects: it does not modify, delete, create, or execute anything. This is a classic Read operation. The description is clear and informative, supporting high confidence.
From the tool's definition Tool description explicitly states it 'Search[es] notes by meaning' and 'returns the best chunk as the snippet source' — a pure retrieval operation with no modification, deletion, or execution of code/commands.
Risk signalsBulk/mass operation — affects multiple targets
Documented attack patterns abuse exactly the kind of access search_semantic gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Obsidian Mcp Pro, and nothing reaches the server without passing your rules. This is the rule we recommend for search_semantic:
{
"version": "1",
"default": "deny",
"tools": {
"search_semantic": {}
}
}search_semantic is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search notes by meaning rather than keywords. Embeds the query with the configured provider, scores every chunk in the persisted index by cosine similarity, ranks one result per note using the best chunk plus a small top-chunk focus signal, and returns the best chunk as the snippet source. Run. It is categorised as a Read tool in the Obsidian Mcp Pro MCP Server, which means it retrieves data without modifying state.
Register the Obsidian Mcp Pro MCP server in PolicyLayer and add a rule for search_semantic: 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 Obsidian Mcp Pro. Nothing to install.
search_semantic 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_semantic 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_semantic. 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_semantic is provided by the Obsidian Mcp Pro MCP server (rps321321/obsidian-mcp-pro). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Obsidian Mcp Pro, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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41 Obsidian Mcp Pro tools catalogued and risk-classified — across an index of 43,000+ MCP servers.