Call this tool when you need to understand how to update dataset examples in LangSmith.
AI agents use update_examples to create or update resources in LangSmith MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your LangSmith MCP Server environment.
The tool modifies dataset examples within LangSmith's observability platform. This is a Write operation as it creates or modifies data reversibly. The severity is medium because while updates to dataset examples could affect model training or validation processes if those datasets are used for fine-tuning or evaluation, the blast radius is limited to the dataset scope and changes are typically reversible.
From the tool's definition Tool name is 'update_examples' and description states it is for 'update dataset examples in LangSmith', indicating reversible modification of data.
Documented attack patterns abuse exactly the kind of access update_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 update_examples:
{
"version": "1",
"default": "deny",
"tools": {
"update_examples": {
"limits": [
{
"counter": "update_examples_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_examples 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.
Call this tool when you need to understand how to update dataset examples in LangSmith. It is categorised as a Write tool in the LangSmith MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the LangSmith MCP Server MCP server in PolicyLayer and add a rule for update_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.
update_examples 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 update_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 update_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.
update_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.
Free to start. No card required.
15 LangSmith MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.