What can langsmith-mcp-server do?

langsmith trace and run observation via mcp protocol, mcp server lifecycle management and resource discovery, langsmith api authentication and credential management, trace and run data retrieval with filtering and pagination, structured trace metadata extraction and serialization, error handling and diagnostic reporting for api failures

langsmith-mcp-server

MCP ServerFree

LangSmith MCP Server - TypeScript implementation

Open Source

/ 100

6 capabilities

Capabilities6 decomposed

langsmith trace and run observation via mcp protocol

Medium confidence

Exposes LangSmith's trace and run APIs through the Model Context Protocol (MCP), allowing Claude and other MCP-compatible clients to observe, query, and analyze LLM execution traces without direct SDK integration. Implements MCP resource and tool handlers that translate client requests into LangSmith REST API calls, with automatic authentication via API key management and response serialization back to the MCP client.

Solves for

Query execution traces and runs from Claude without leaving the conversation contextInspect LLM chain execution details, token counts, and latency metrics during debuggingRetrieve historical run data to analyze model behavior patterns across multiple invocationsAccess structured trace metadata for post-hoc analysis and observability reporting

Best for

LLM application developers using Claude as their primary development interface

Teams building multi-agent systems who need real-time observability into LangSmith traces

Developers integrating LangSmith observability into MCP-based AI workflows

Requires

Node.js 16+ runtime

LangSmith API key (from https://smith.langchain.com)

MCP-compatible client (Claude Desktop, or other MCP host)

Limitations

Read-only access to traces and runs — cannot create or modify traces through MCP interface

Latency depends on LangSmith API response times; no local caching of trace data

Requires valid LangSmith API key with appropriate permissions; no fallback for unauthenticated access

What makes it unique

Bridges LangSmith observability into the MCP ecosystem, enabling Claude and other MCP clients to query production traces and runs natively without SDK boilerplate. Uses MCP's resource and tool abstractions to expose LangSmith's REST API surface as first-class capabilities within the client's context window.

vs alternatives

Provides observability access directly within Claude's conversation context via MCP, whereas direct LangSmith SDK usage requires separate Python/JS code execution and context switching.

mcp server lifecycle management and resource discovery

Medium confidence

Implements the MCP server specification for TypeScript, handling protocol initialization, capability negotiation, and resource/tool registration. Manages the request-response cycle for MCP clients, including proper error handling, timeout management, and graceful shutdown. Provides introspectable resource and tool schemas that allow clients to discover available LangSmith operations and their parameters.

Solves for

Start and configure an MCP server that exposes LangSmith capabilities to Claude Desktop or other MCP hostsDiscover available LangSmith operations and their required parameters from within an MCP clientHandle connection lifecycle events and ensure clean shutdown of the server processValidate incoming MCP requests and return properly formatted responses

Best for

Developers setting up local MCP servers for Claude Desktop integration

Teams deploying MCP servers in containerized or serverless environments

Builders creating MCP-based observability dashboards or automation workflows

Requires

Node.js 16+

TypeScript 4.5+ (if building from source)

MCP client that supports the MCP specification (e.g., Claude Desktop 0.1+)

Limitations

Single-threaded request handling — concurrent requests are queued sequentially

No built-in load balancing or horizontal scaling; designed for single-client or low-concurrency scenarios

Requires explicit server startup and configuration; no auto-discovery mechanism for MCP hosts

What makes it unique

Implements the full MCP server specification in TypeScript with proper protocol negotiation and resource schema advertisement, allowing seamless integration with Claude Desktop and other MCP-compatible hosts. Uses standard MCP patterns for tool and resource registration rather than custom RPC mechanisms.

vs alternatives

Provides standards-compliant MCP server implementation, whereas custom REST or WebSocket servers would require clients to implement their own protocol handling and discovery logic.

langsmith api authentication and credential management

Medium confidence

Manages LangSmith API authentication by accepting and validating API keys, constructing properly authenticated HTTP requests to the LangSmith API, and handling token refresh or expiration scenarios. Stores credentials securely (typically via environment variables or MCP configuration) and injects them into all outbound requests as Authorization headers. Implements error handling for authentication failures with clear diagnostic messages.

Solves for

Authenticate requests to LangSmith API using a valid API key without exposing credentials in logsHandle authentication errors gracefully and provide actionable error messages when credentials are invalid or expiredSupport multiple authentication methods or credential sources (environment variables, config files, MCP parameters)Ensure all LangSmith API calls include proper authorization headers

Best for

Developers deploying MCP servers in shared or production environments where credential security is critical

Teams managing multiple LangSmith projects with different API keys per environment

Builders integrating LangSmith observability into larger MCP-based automation systems

Requires

Valid LangSmith API key from https://smith.langchain.com/settings/api-keys

Environment variable or MCP configuration mechanism to pass credentials securely

HTTPS connectivity to api.smith.langchain.com

Limitations

Credentials must be provided at server startup; no runtime credential rotation without server restart

No built-in credential encryption — relies on OS-level environment variable security

API key is transmitted in plaintext over HTTPS; vulnerable if HTTPS is compromised

What makes it unique

Integrates LangSmith API authentication directly into the MCP server lifecycle, allowing credentials to be managed at the server level rather than per-request. Uses standard HTTP Authorization header patterns and delegates credential storage to the MCP host's configuration mechanism.

vs alternatives

Centralizes authentication at the MCP server level, whereas client-side authentication would require each MCP client to manage credentials separately and risk exposing them in client logs.

trace and run data retrieval with filtering and pagination

Medium confidence

Implements MCP tools and resources that query the LangSmith API for trace and run data, supporting filtering by project, date range, status, and other metadata. Handles pagination of large result sets and transforms LangSmith's REST API responses into structured JSON suitable for MCP clients. Supports both resource-based access (fetch a specific trace by ID) and tool-based queries (search runs by criteria).

Solves for

Retrieve a specific trace or run by ID to inspect its execution details and metadataSearch for runs matching specific criteria (project, date range, status) to analyze patternsPaginate through large result sets without loading all data into memory at onceExport trace data in a structured format for analysis or reporting

Best for

Developers debugging specific LLM invocations by querying their traces from Claude

Teams analyzing run performance metrics across multiple projects

Builders creating observability dashboards or automated alerting based on trace data

Requires

Valid LangSmith API key with read access to traces and runs

Project ID or name to filter results (if querying specific projects)

Network access to api.smith.langchain.com

Limitations

Query performance depends on LangSmith API response times; no local indexing or caching

Pagination requires explicit offset/limit parameters; no cursor-based pagination support

Large trace objects (with full token logs) may exceed MCP message size limits

What makes it unique

Exposes LangSmith's trace and run query APIs through MCP's resource and tool abstractions, allowing Claude to retrieve and filter observability data using natural language queries that are translated into structured API calls. Handles response transformation and pagination transparently.

vs alternatives

Provides query access to LangSmith traces directly within Claude's context, whereas the LangSmith UI or direct API calls require context switching and manual query construction.

structured trace metadata extraction and serialization

Medium confidence

Transforms raw LangSmith trace and run objects into structured JSON that preserves key metadata (timestamps, token counts, latency, error messages, input/output payloads) while filtering out internal or verbose fields. Implements custom serialization logic to handle nested objects, arrays, and special types (dates, errors) in a way that's suitable for MCP message transmission. Ensures output is deterministic and suitable for downstream analysis or logging.

Solves for

Extract key metrics from traces (latency, token usage, cost) for performance analysisSerialize trace data into a compact JSON format suitable for MCP message transmissionPreserve error messages and stack traces from failed runs for debuggingFormat trace metadata for human-readable display in Claude or other MCP clients

Best for

Developers analyzing LLM performance metrics and token usage patterns

Teams building observability dashboards that consume trace data from MCP

Builders creating automated alerting or anomaly detection based on trace metrics

Requires

Raw trace or run objects from LangSmith API

Knowledge of which fields are relevant for the use case

Limitations

Serialization may truncate very large payloads (e.g., full token logs) to fit MCP message size limits

Custom serialization logic may not preserve all LangSmith fields; some metadata may be lost

Nested object depth is limited by MCP message size constraints

What makes it unique

Implements custom serialization logic tailored to MCP message constraints, filtering and transforming LangSmith's verbose trace objects into compact, structured JSON suitable for transmission and analysis. Preserves key observability metrics while dropping internal fields.

vs alternatives

Provides automatic transformation of LangSmith API responses into MCP-compatible format, whereas raw API access would require clients to implement their own serialization and filtering logic.

error handling and diagnostic reporting for api failures

Medium confidence

Implements comprehensive error handling for LangSmith API failures, including HTTP error codes (401, 403, 404, 500), network timeouts, and malformed responses. Translates LangSmith API errors into MCP-compatible error responses with diagnostic codes and human-readable messages. Logs errors for debugging while avoiding credential leakage in error messages.

Solves for

Diagnose authentication failures (invalid or expired API key) with clear error messagesHandle API rate limiting gracefully and inform clients when to retryReport network or connectivity issues without exposing internal server detailsProvide actionable error messages that guide developers toward resolution

Best for

Developers troubleshooting MCP server connectivity or LangSmith API issues

Teams deploying MCP servers in production and needing robust error reporting

Builders creating automated error handling or retry logic in MCP clients

Requires

Network connectivity to api.smith.langchain.com

Proper error handling in MCP client to interpret error responses

Limitations

Error messages may not include full context from LangSmith API; some details are filtered for security

No automatic retry logic; clients must implement their own retry strategies

Timeout handling depends on Node.js HTTP client defaults; not configurable per request

What makes it unique

Implements MCP-aware error handling that translates LangSmith API errors into MCP protocol-compliant error responses, with diagnostic codes and messages suitable for both automated handling and human debugging. Filters sensitive information (credentials, internal paths) from error messages.

vs alternatives

Provides standardized error reporting through MCP protocol, whereas direct API access would require clients to parse and handle LangSmith's native error format.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with langsmith-mcp-server, ranked by overlap. Discovered automatically through the match graph.

MCP Server44

@langchain/mcp-adapters

LangChain.js adapters for Model Context Protocol (MCP)

mcp client lifecycle managementmcp server-to-langchain tool adaptertool execution tracing and observability

3 shared capabilities

MCP Server47

@langchain/mcp-adapters

LangChain.js adapters for Model Context Protocol (MCP)

mcp server capability discovery and introspectionmcp server-to-langchain tool adaptermcp transport abstraction layer

3 shared capabilities

Framework48

Langflow

Visual multi-agent and RAG builder — drag-and-drop flows with Python and LangChain components.

tracing and observability with langsmith integrationmodel context protocol (mcp) integration for tool and resource discovery

2 shared capabilities

MCP Server24

cls-mcp-server

[![npm version](https://img.shields.io/npm/v/cls-mcp-server)](https://www.npmjs.com/package/cls-mcp-server) [![license](https://img.shields.io/npm/l/cls-mcp-server)](https://github.com/Tencent/cls-mcp-server/blob/v1.0.2/LICENSE)

authentication and credential management for mcp transportmcp server initialization and lifecycle management

2 shared capabilities

Framework19

LangChain

A framework for developing applications powered by language models.

langsmith observability and tracing integration

1 shared capability

Framework25

langchain-openai

An integration package connecting OpenAI and LangChain

langsmith integration for tracing and debugging

1 shared capability

Best For

✓LLM application developers using Claude as their primary development interface
✓Teams building multi-agent systems who need real-time observability into LangSmith traces
✓Developers integrating LangSmith observability into MCP-based AI workflows
✓Developers setting up local MCP servers for Claude Desktop integration
✓Teams deploying MCP servers in containerized or serverless environments
✓Builders creating MCP-based observability dashboards or automation workflows
✓Developers deploying MCP servers in shared or production environments where credential security is critical
✓Teams managing multiple LangSmith projects with different API keys per environment

Known Limitations

⚠Read-only access to traces and runs — cannot create or modify traces through MCP interface
⚠Latency depends on LangSmith API response times; no local caching of trace data
⚠Requires valid LangSmith API key with appropriate permissions; no fallback for unauthenticated access
⚠MCP protocol overhead adds ~50-200ms per request compared to direct SDK calls
⚠Single-threaded request handling — concurrent requests are queued sequentially
⚠No built-in load balancing or horizontal scaling; designed for single-client or low-concurrency scenarios

Requirements

Node.js 16+ runtimeLangSmith API key (from https://smith.langchain.com)MCP-compatible client (Claude Desktop, or other MCP host)Network access to api.smith.langchain.comNode.js 16+TypeScript 4.5+ (if building from source)MCP client that supports the MCP specification (e.g., Claude Desktop 0.1+)Valid LangSmith API key from https://smith.langchain.com/settings/api-keys

Input / Output

Accepts: MCP tool calls with JSON parameters (run IDs, trace IDs, filter criteria), MCP resource URIs identifying specific traces or runs, MCP initialization messages with client capabilities, MCP tool call requests with JSON parameters, MCP resource read requests with URI identifiers, API key string (typically 32-64 characters), MCP configuration parameters or environment variables, Trace or run ID (UUID string), Filter parameters: project name, date range, status, tags, Pagination parameters: offset, limit, LangSmith trace objects (JSON from API), LangSmith run objects (JSON from API), Configuration specifying which fields to include/exclude, HTTP error responses from LangSmith API, Network timeouts or connection failures, Malformed or unexpected API responses

Produces: JSON-serialized trace objects with execution metadata, Structured run data including timestamps, inputs, outputs, and token counts, Error responses with diagnostic information, MCP capability advertisements (list of available tools and resources), MCP tool execution results with JSON payloads, MCP error responses with diagnostic codes, Authenticated HTTP requests with Authorization headers, Authentication error responses with diagnostic codes (401, 403), Trace objects with execution metadata, inputs, outputs, and token counts, Run objects with status, duration, and error information, Paginated result sets with total count and has_more indicators, Serialized JSON with flattened metadata, Formatted timestamp strings (ISO 8601 or custom format), Aggregated metrics (total tokens, latency, cost), MCP error responses with diagnostic codes (e.g., 'INVALID_API_KEY', 'RATE_LIMITED'), Human-readable error messages, Retry-after hints for rate-limited requests

UnfragileRank

Adoption15%(30% weight)

Quality14%(25% weight)

Ecosystem40%(25% weight)

Match Graph10%(15% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

6 capabilities

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Package Details

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0.1.7

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LangSmith MCP Server - TypeScript implementation

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Capabilities6 decomposed

langsmith trace and run observation via mcp protocol

Medium confidence

Solves for

Best for

LLM application developers using Claude as their primary development interface

Teams building multi-agent systems who need real-time observability into LangSmith traces

Developers integrating LangSmith observability into MCP-based AI workflows

Requires

Node.js 16+ runtime

LangSmith API key (from https://smith.langchain.com)

MCP-compatible client (Claude Desktop, or other MCP host)

Limitations

Read-only access to traces and runs — cannot create or modify traces through MCP interface

Latency depends on LangSmith API response times; no local caching of trace data

Requires valid LangSmith API key with appropriate permissions; no fallback for unauthenticated access

What makes it unique

vs alternatives

Provides observability access directly within Claude's conversation context via MCP, whereas direct LangSmith SDK usage requires separate Python/JS code execution and context switching.

mcp server lifecycle management and resource discovery

Medium confidence

Solves for

Best for

Developers setting up local MCP servers for Claude Desktop integration

Teams deploying MCP servers in containerized or serverless environments

Builders creating MCP-based observability dashboards or automation workflows

Requires

Node.js 16+

TypeScript 4.5+ (if building from source)

MCP client that supports the MCP specification (e.g., Claude Desktop 0.1+)

Limitations

Single-threaded request handling — concurrent requests are queued sequentially

No built-in load balancing or horizontal scaling; designed for single-client or low-concurrency scenarios

Requires explicit server startup and configuration; no auto-discovery mechanism for MCP hosts

What makes it unique

vs alternatives

Provides standards-compliant MCP server implementation, whereas custom REST or WebSocket servers would require clients to implement their own protocol handling and discovery logic.

langsmith api authentication and credential management

Medium confidence

Solves for

Best for

Developers deploying MCP servers in shared or production environments where credential security is critical

Teams managing multiple LangSmith projects with different API keys per environment

Builders integrating LangSmith observability into larger MCP-based automation systems

Requires

Valid LangSmith API key from https://smith.langchain.com/settings/api-keys

Environment variable or MCP configuration mechanism to pass credentials securely

HTTPS connectivity to api.smith.langchain.com

Limitations

Credentials must be provided at server startup; no runtime credential rotation without server restart

No built-in credential encryption — relies on OS-level environment variable security

API key is transmitted in plaintext over HTTPS; vulnerable if HTTPS is compromised

What makes it unique

vs alternatives

Centralizes authentication at the MCP server level, whereas client-side authentication would require each MCP client to manage credentials separately and risk exposing them in client logs.

trace and run data retrieval with filtering and pagination

Medium confidence

Solves for

Best for

Developers debugging specific LLM invocations by querying their traces from Claude

Teams analyzing run performance metrics across multiple projects

Builders creating observability dashboards or automated alerting based on trace data

Requires

Valid LangSmith API key with read access to traces and runs

Project ID or name to filter results (if querying specific projects)

Network access to api.smith.langchain.com

Limitations

Query performance depends on LangSmith API response times; no local indexing or caching

Pagination requires explicit offset/limit parameters; no cursor-based pagination support

Large trace objects (with full token logs) may exceed MCP message size limits

What makes it unique

vs alternatives

Provides query access to LangSmith traces directly within Claude's context, whereas the LangSmith UI or direct API calls require context switching and manual query construction.

structured trace metadata extraction and serialization

Medium confidence

Solves for

Best for

Developers analyzing LLM performance metrics and token usage patterns

Teams building observability dashboards that consume trace data from MCP

Builders creating automated alerting or anomaly detection based on trace metrics

Requires

Raw trace or run objects from LangSmith API

Knowledge of which fields are relevant for the use case

Limitations

Serialization may truncate very large payloads (e.g., full token logs) to fit MCP message size limits

Custom serialization logic may not preserve all LangSmith fields; some metadata may be lost

Nested object depth is limited by MCP message size constraints

What makes it unique

vs alternatives

Provides automatic transformation of LangSmith API responses into MCP-compatible format, whereas raw API access would require clients to implement their own serialization and filtering logic.

error handling and diagnostic reporting for api failures

Medium confidence

Solves for

Best for

Developers troubleshooting MCP server connectivity or LangSmith API issues

Teams deploying MCP servers in production and needing robust error reporting

Builders creating automated error handling or retry logic in MCP clients

Requires

Network connectivity to api.smith.langchain.com

Proper error handling in MCP client to interpret error responses

Limitations

Error messages may not include full context from LangSmith API; some details are filtered for security

No automatic retry logic; clients must implement their own retry strategies

Timeout handling depends on Node.js HTTP client defaults; not configurable per request

What makes it unique

vs alternatives

Provides standardized error reporting through MCP protocol, whereas direct API access would require clients to parse and handle LangSmith's native error format.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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Compare →

langsmith-mcp-server

Capabilities6 decomposed

langsmith trace and run observation via mcp protocol

mcp server lifecycle management and resource discovery

langsmith api authentication and credential management

trace and run data retrieval with filtering and pagination

structured trace metadata extraction and serialization

error handling and diagnostic reporting for api failures

Related Artifactssharing capabilities

@langchain/mcp-adapters

@langchain/mcp-adapters

Langflow

cls-mcp-server

LangChain

langchain-openai

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

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langsmith-mcp-server

Capabilities6 decomposed

langsmith trace and run observation via mcp protocol

mcp server lifecycle management and resource discovery

langsmith api authentication and credential management

trace and run data retrieval with filtering and pagination

structured trace metadata extraction and serialization

error handling and diagnostic reporting for api failures

Related Artifactssharing capabilities

@langchain/mcp-adapters

@langchain/mcp-adapters

Langflow

cls-mcp-server

LangChain

langchain-openai

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to langsmith-mcp-server

Are you the builder of langsmith-mcp-server?

Get the weekly brief

Data Sources