A
licenseNot graded
qualityC
maintenanceEnables AI agents to access observability and evaluation data, including run history, span traces, LLM-as-judge evaluation results, and regression reports.
MIT
LangSmith MCP Server
Officialby langchain-ai
Related Servers
Alternatives to LangSmith MCP Server
No user-submitted related servers found.
Related Servers
- FlicenseAqualityDmaintenanceEnables read-only querying of LangSmith traces including runs, children, and URLs without extra instrumentation.51-
- AlicenseBqualityCmaintenanceEnables LLM agents to query Weights & Biases experiments, including listing projects, runs, metrics, plotting metrics, and retrieving run details.51MIT
- FlicenseNot gradedqualityDmaintenanceEnables LLMs to interact with Hopsworks for platform management, feature store operations, model lifecycle, jobs, and integrations.-
- AlicenseNot gradedqualityBmaintenanceEnables coding agents to access live runtime observability data such as logs, deploys, and health metrics for evidence-based incident triage.1MIT
- AlicenseAqualityDmaintenanceEnables LLMs to query telemetry data via the Spyglass AI agent, providing intelligent insights about application performance, errors, and bottlenecks.1MIT
TDQS
A3.5/5.0
Scored across 13 tools
Disambiguation4/5
Most tools have distinct purposes targeting different LangSmith resources like datasets, examples, prompts, runs, projects, and experiments, with clear boundaries. However, 'create_dataset' and 'push_prompt' are described as informational tools ('call this tool when you need to understand how to...'), which could confuse agents about their actual functionality versus other tools that perform operations directly.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, such as 'create_dataset', 'fetch_runs', 'list_datasets', 'read_example', and 'update_examples'. All tools use snake_case with clear, descriptive names, making the set predictable and easy to navigate.
Tool Count5/5
With 13 tools, the server is well-scoped for managing LangSmith resources, covering datasets, examples, prompts, runs, projects, and experiments. Each tool serves a specific function without redundancy, and the count aligns with the complexity of the domain, providing comprehensive coverage without being overwhelming.
Completeness4/5
The tool set offers strong coverage for core LangSmith operations, including CRUD-like actions for datasets, examples, prompts, runs, projects, and experiments. Minor gaps exist, such as no explicit 'delete' tools for resources like datasets or prompts, but agents can likely work around this given the overall robust surface for analytics and management tasks.
Maintenance
ActivitySlowing
ResponsivenessUnresponsive