AI agents call list_examples to retrieve information from LangSmith MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves or queries data from the LangSmith observability platform with no side effects. No creation, modification, deletion, code execution, or financial operations are implied. The empty description slightly lowers confidence, but the naming convention and server context strongly suggest this is a read operation consistent with other 'list_*' tools on the same server.
From the tool's definition Tool name 'list_examples' and server context indicate retrieval of examples from LangSmith datasets. The 'list' prefix and sibling tools (list_datasets, list_experiments, list_projects, list_prompts) confirm this is a read-only query operation.
Documented attack patterns abuse exactly the kind of access list_examples gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and LangSmith MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_examples:
{
"version": "1",
"default": "deny",
"tools": {
"list_examples": {}
}
}list_examples is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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list_examples. It is categorised as a Read tool in the LangSmith MCP Server MCP Server, which means it retrieves data without modifying state.
Register the LangSmith MCP Server MCP server in PolicyLayer and add a rule for list_examples: 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 LangSmith MCP Server. Nothing to install.
list_examples 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 list_examples 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 list_examples. 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.
list_examples is provided by the LangSmith MCP Server MCP server (langchain-ai/langsmith-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from LangSmith MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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15 LangSmith MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.