What can @launchdarkly/mcp-server do?

feature flag state querying via mcp tools, feature flag crud operations via mcp resources, environment-aware flag evaluation context, user targeting and segment evaluation, flag analytics and audit trail access, flag variation schema and metadata inspection, mcp server lifecycle and configuration management

@launchdarkly/mcp-server

MCP ServerFree

The official [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server for [LaunchDarkly](https://launchdarkly.com/).

Open Source

/ 100

7 capabilities

Capabilities7 decomposed

feature flag state querying via mcp tools

Medium confidence

Exposes LaunchDarkly feature flags as callable MCP tools that LLM agents can invoke to check flag status, variations, and metadata. Implements the MCP tool schema specification with LaunchDarkly SDK integration, allowing agents to query flag state in real-time without direct API calls. The server translates MCP tool invocations into LaunchDarkly SDK method calls, returning structured flag evaluation results with context awareness for users, environments, and custom attributes.

Solves for

Query whether a feature flag is enabled for a specific user or context within an LLM agent workflowRetrieve the current variation value of a flag to conditionally execute agent actionsCheck flag metadata and targeting rules to inform agent decision-makingIntegrate feature flag state into multi-step agent reasoning chains

Best for

AI agents and LLM applications that need runtime feature flag decisions

Teams building AI-driven deployment or release management systems

Developers integrating LaunchDarkly into Claude, ChatGPT, or other LLM-based workflows

Requires

LaunchDarkly account with API access

LaunchDarkly SDK for Node.js (JavaScript/TypeScript)

Valid LaunchDarkly SDK key (client-side or server-side)

Limitations

Requires active LaunchDarkly SDK client initialization — no lazy loading or connection pooling abstraction

Flag evaluation latency depends on LaunchDarkly SDK caching strategy; real-time flag changes may have propagation delay

No built-in pagination or batching for querying multiple flags simultaneously — each tool call is a single flag lookup

What makes it unique

Native MCP tool binding for LaunchDarkly SDK that exposes flag evaluation as first-class agent capabilities, with structured schema mapping between LaunchDarkly evaluation context and MCP tool parameters — eliminates need for agents to construct raw API calls or manage SDK lifecycle

vs alternatives

Provides direct SDK-level flag evaluation within agent workflows vs. requiring agents to call LaunchDarkly REST API directly, reducing latency and simplifying context passing

feature flag crud operations via mcp resources

Medium confidence

Exposes LaunchDarkly flag creation, update, and deletion as MCP resources or tools, allowing agents to programmatically manage flags without direct dashboard access. Implements write operations through the LaunchDarkly Management API, with schema validation and error handling for flag configuration changes. The server translates agent requests into API calls that modify flag targeting rules, variations, and metadata, returning confirmation and updated flag state.

Solves for

Create new feature flags programmatically from agent workflowsUpdate flag targeting rules or variations based on agent decisionsDelete or archive flags when features are deprecatedBulk modify flag configurations across environments

Best for

Automated release management systems powered by AI agents

Teams building self-service flag management interfaces backed by LLMs

DevOps workflows that need AI-driven flag lifecycle management

Requires

LaunchDarkly account with Management API access

LaunchDarkly Management API key (write-enabled)

MCP client with tool-calling support

Limitations

Requires LaunchDarkly Management API key with write permissions — broader credential scope than read-only flag evaluation

No transactional guarantees for multi-flag updates — partial failures possible if one flag update fails

API rate limits apply; high-frequency flag modifications may hit LaunchDarkly API throttling

What makes it unique

Wraps LaunchDarkly Management API in MCP tool schema, enabling agents to perform flag lifecycle management with structured input validation and error handling — abstracts API complexity while maintaining full flag configuration control

vs alternatives

Allows agents to modify flags programmatically vs. requiring manual dashboard interaction or custom REST API integration, reducing operational overhead

environment-aware flag evaluation context

Medium confidence

Manages context switching across LaunchDarkly environments (dev, staging, production) within a single MCP server instance, allowing agents to evaluate flags against different deployment targets. Implements environment routing through MCP tool parameters or resource paths, with SDK client management per environment. The server maintains separate flag evaluation contexts per environment, ensuring agents can compare flag states across environments or target specific deployment stages.

Solves for

Evaluate a flag in production vs. staging to compare rollout behaviorRoute agent decisions to different environments based on risk or deployment stageTest flag configurations in dev before promoting to productionImplement multi-environment deployment workflows with flag-driven logic

Best for

Teams with multi-environment deployments (dev/staging/prod) using LaunchDarkly

Agents managing progressive rollouts across environments

Organizations needing environment-specific flag evaluation in AI workflows

Requires

LaunchDarkly SDK keys for each target environment

MCP client capable of passing environment parameters

Knowledge of valid environment identifiers in LaunchDarkly project

Limitations

Requires separate LaunchDarkly SDK keys per environment — no single credential for cross-environment access

Environment context must be explicitly specified in each tool call; no implicit environment inheritance

SDK client initialization per environment adds memory overhead and startup latency

What makes it unique

Implements environment routing at the MCP server level with per-environment SDK client management, allowing agents to seamlessly switch evaluation contexts without managing multiple LaunchDarkly connections — abstracts environment complexity into tool parameters

vs alternatives

Enables cross-environment flag comparison within a single agent workflow vs. requiring separate API calls or manual environment switching

user targeting and segment evaluation

Medium confidence

Evaluates feature flags against specific users or user segments defined in LaunchDarkly, with support for custom user attributes and targeting rules. Implements user context construction through MCP tool parameters, translating agent-provided user data into LaunchDarkly evaluation context. The server applies flag targeting logic (user ID matching, segment membership, custom attribute rules) and returns personalized flag states for individual users or user cohorts.

Solves for

Check if a specific user is in a flag's target audienceEvaluate flags for users with custom attributes (e.g., subscription tier, region)Determine flag state for user segments (e.g., beta testers, enterprise customers)Build user-aware agent workflows that adapt behavior based on flag targeting

Best for

Personalization engines that need flag-driven user experiences

A/B testing workflows where agents need to know user assignment

User segmentation systems integrated with feature flags

Requires

LaunchDarkly SDK with user context support

User attributes pre-configured in LaunchDarkly project

User ID or identifying information available to agent

Limitations

User attributes must be pre-defined in LaunchDarkly; agents cannot dynamically create new attribute types

Segment membership is evaluated server-side; agents cannot directly query segment definitions

Custom attribute values are limited to LaunchDarkly's supported types (string, number, boolean, array) — complex objects not supported

What makes it unique

Encapsulates LaunchDarkly's user targeting and segment evaluation logic as MCP tools, allowing agents to make user-aware decisions without understanding targeting rule syntax — automatically applies custom attribute matching and segment membership checks

vs alternatives

Provides user-aware flag evaluation vs. generic flag queries, enabling agents to personalize behavior based on LaunchDarkly's targeting rules

flag analytics and audit trail access

Medium confidence

Exposes LaunchDarkly flag analytics (flag usage, variation distribution, user exposure) and audit logs (flag change history, who modified what) as MCP resources, allowing agents to query flag performance and governance data. Implements read-only access to LaunchDarkly Events API and audit endpoints, returning structured analytics and change history. The server aggregates flag metrics and audit records, enabling agents to make data-driven decisions about flag rollouts or identify configuration drift.

Solves for

Query flag usage metrics to determine if a flag is actively used before deprecationCheck variation distribution to understand rollout success or user adoptionReview flag change history to audit who modified targeting rules and whenIdentify flags with unusual patterns (e.g., high error rates, unexpected variation distribution)

Best for

Governance and compliance workflows that need flag audit trails

Analytics-driven agents that optimize rollouts based on usage metrics

Teams implementing flag lifecycle management with historical tracking

Requires

LaunchDarkly account with analytics/audit API access

LaunchDarkly SDK or API key with read permissions

MCP client capable of handling time-series or historical data

Limitations

Analytics data may be delayed by 5-15 minutes depending on LaunchDarkly's data pipeline

Audit logs are limited to recent changes (typically 90 days retention) — no long-term historical analysis

Variation distribution metrics are aggregated; no per-user variation tracking for privacy reasons

What makes it unique

Aggregates LaunchDarkly analytics and audit APIs into MCP resources, providing agents with historical flag performance and governance data — enables data-driven flag management decisions without direct API knowledge

vs alternatives

Allows agents to access flag analytics and audit trails vs. requiring manual dashboard inspection or separate analytics API integration

flag variation schema and metadata inspection

Medium confidence

Provides introspection into flag definitions, including variation schemas, targeting rules, and metadata, allowing agents to understand flag structure before evaluation. Implements flag metadata retrieval through LaunchDarkly SDK or API, returning flag configuration details (variation types, defaults, descriptions). The server enables agents to discover available flags, understand their variations, and validate inputs before making evaluation calls.

Solves for

Discover all available flags in a project to understand feature landscapeInspect flag variation types to construct valid evaluation contextsRead flag descriptions and metadata to understand intent and usageValidate flag keys and variation values before making evaluation calls

Best for

Agents that need to dynamically discover and adapt to flag configurations

Self-service flag management interfaces that expose flag metadata

Development workflows where agents need to understand flag structure

Requires

LaunchDarkly SDK with flag metadata access

API key with read permissions

MCP client capable of handling nested JSON structures

Limitations

Flag metadata is static at query time; changes require re-fetching

No schema validation for custom variation types — agents must interpret variation structure

Targeting rule details may be complex; agents cannot easily understand rule logic from metadata alone

What makes it unique

Exposes LaunchDarkly flag metadata as queryable MCP resources, enabling agents to discover and understand flag structure dynamically — acts as a knowledge base for flag definitions within agent workflows

vs alternatives

Allows agents to introspect flag configurations vs. requiring hardcoded flag knowledge or manual documentation lookup

mcp server lifecycle and configuration management

Medium confidence

Manages MCP server initialization, configuration, and connection lifecycle for LaunchDarkly integration. Implements server setup through environment variables or configuration files, handling LaunchDarkly SDK client initialization, credential management, and MCP protocol compliance. The server exposes configuration options for environment selection, API key management, and tool/resource registration, enabling flexible deployment across different LaunchDarkly projects and environments.

Solves for

Initialize MCP server with LaunchDarkly credentials and environment configurationSwitch between different LaunchDarkly projects or environments without restartingConfigure which tools and resources are exposed to MCP clientsManage server lifecycle (startup, shutdown, health checks)

Best for

DevOps teams deploying MCP servers for LaunchDarkly integration

Developers integrating the MCP server into Claude Desktop or other MCP clients

Teams managing multiple LaunchDarkly projects with different server instances

Requires

Node.js 16+ (or compatible JavaScript runtime)

LaunchDarkly SDK for Node.js

MCP server library (@modelcontextprotocol/sdk)

Limitations

Configuration is static at server startup; runtime configuration changes require restart

No built-in credential rotation — credentials must be manually updated and server restarted

Environment variables are the primary configuration method; no dynamic configuration API

What makes it unique

Implements MCP server lifecycle management with LaunchDarkly SDK integration, handling credential management and tool registration — abstracts MCP protocol complexity from LaunchDarkly integration logic

vs alternatives

Provides out-of-the-box MCP server setup for LaunchDarkly vs. requiring custom MCP server implementation

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

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Manage Supabase databases, auth, and storage via MCP.

feature group-based tool configuration and selective capability enablement

1 shared capability

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Label Studio

Open-source multi-modal data labeling platform.

feature flag system for gradual feature rollout and a/b testing

1 shared capability

Best For

✓AI agents and LLM applications that need runtime feature flag decisions
✓Teams building AI-driven deployment or release management systems
✓Developers integrating LaunchDarkly into Claude, ChatGPT, or other LLM-based workflows
✓Automated release management systems powered by AI agents
✓Teams building self-service flag management interfaces backed by LLMs
✓DevOps workflows that need AI-driven flag lifecycle management
✓Teams with multi-environment deployments (dev/staging/prod) using LaunchDarkly
✓Agents managing progressive rollouts across environments

Known Limitations

⚠Requires active LaunchDarkly SDK client initialization — no lazy loading or connection pooling abstraction
⚠Flag evaluation latency depends on LaunchDarkly SDK caching strategy; real-time flag changes may have propagation delay
⚠No built-in pagination or batching for querying multiple flags simultaneously — each tool call is a single flag lookup
⚠Context attributes must be manually constructed and passed; no automatic context inference from agent state
⚠Requires LaunchDarkly Management API key with write permissions — broader credential scope than read-only flag evaluation
⚠No transactional guarantees for multi-flag updates — partial failures possible if one flag update fails

Requirements

LaunchDarkly account with API accessLaunchDarkly SDK for Node.js (JavaScript/TypeScript)Valid LaunchDarkly SDK key (client-side or server-side)MCP client implementation (Claude Desktop, Cline, or compatible tool)LaunchDarkly account with Management API accessLaunchDarkly Management API key (write-enabled)MCP client with tool-calling supportUnderstanding of LaunchDarkly flag configuration schema

Input / Output

Accepts: flag key (string), user/context object (JSON with user ID, custom attributes), environment identifier (string), flag configuration object (JSON with key, name, variations, targeting rules), targeting rule specification (JSON), environment identifier (string: 'dev', 'staging', 'production'), user/context object (JSON), user ID (string), custom attributes (JSON object with key-value pairs), segment identifiers (string array, optional), time range (ISO 8601 dates or relative time), environment identifier (string, optional), flag key (string, optional — if omitted, returns all flags), environment variables (LAUNCHDARKLY_SDK_KEY, LAUNCHDARKLY_API_KEY, etc.), configuration file (JSON or YAML, if supported)

Produces: boolean (flag on/off), variation value (any JSON type), flag metadata (name, description, targeting rules), flag creation response (flag ID, metadata), update confirmation (modified flag state), error details (validation failures, API errors), flag evaluation result per environment (boolean or variation value), environment metadata (name, description), flag state for user (boolean or variation value), user segment membership (boolean per segment), targeting rule match details (which rules applied), flag usage metrics (JSON with counts, timestamps), variation distribution (JSON with percentages per variation), audit log entries (JSON array with change details, timestamps, user info), flag metadata (JSON with key, name, description, variations, defaults), variation schema (JSON describing variation types and structure), targeting rule summary (high-level description of targeting logic), server startup confirmation, registered tools and resources list, connection status (ready for MCP clients)

UnfragileRank

Adoption48%(25% weight)

Quality24%(25% weight)

Ecosystem45%(15% weight)

Match Graph25%(30% 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

7 capabilities

Visit @launchdarkly/mcp-server→

Package Details

npm

Registry

0.6.1

Version

12,352

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About

The official [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server for [LaunchDarkly](https://launchdarkly.com/).

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Capabilities7 decomposed

feature flag state querying via mcp tools

Medium confidence

Solves for

Best for

AI agents and LLM applications that need runtime feature flag decisions

Teams building AI-driven deployment or release management systems

Developers integrating LaunchDarkly into Claude, ChatGPT, or other LLM-based workflows

Requires

LaunchDarkly account with API access

LaunchDarkly SDK for Node.js (JavaScript/TypeScript)

Valid LaunchDarkly SDK key (client-side or server-side)

Limitations

Requires active LaunchDarkly SDK client initialization — no lazy loading or connection pooling abstraction

Flag evaluation latency depends on LaunchDarkly SDK caching strategy; real-time flag changes may have propagation delay

No built-in pagination or batching for querying multiple flags simultaneously — each tool call is a single flag lookup

What makes it unique

vs alternatives

Provides direct SDK-level flag evaluation within agent workflows vs. requiring agents to call LaunchDarkly REST API directly, reducing latency and simplifying context passing

feature flag crud operations via mcp resources

Medium confidence

Solves for

Best for

Automated release management systems powered by AI agents

Teams building self-service flag management interfaces backed by LLMs

DevOps workflows that need AI-driven flag lifecycle management

Requires

LaunchDarkly account with Management API access

LaunchDarkly Management API key (write-enabled)

MCP client with tool-calling support

Limitations

Requires LaunchDarkly Management API key with write permissions — broader credential scope than read-only flag evaluation

No transactional guarantees for multi-flag updates — partial failures possible if one flag update fails

API rate limits apply; high-frequency flag modifications may hit LaunchDarkly API throttling

What makes it unique

vs alternatives

Allows agents to modify flags programmatically vs. requiring manual dashboard interaction or custom REST API integration, reducing operational overhead

environment-aware flag evaluation context

Medium confidence

Solves for

Best for

Teams with multi-environment deployments (dev/staging/prod) using LaunchDarkly

Agents managing progressive rollouts across environments

Organizations needing environment-specific flag evaluation in AI workflows

Requires

LaunchDarkly SDK keys for each target environment

MCP client capable of passing environment parameters

Knowledge of valid environment identifiers in LaunchDarkly project

Limitations

Requires separate LaunchDarkly SDK keys per environment — no single credential for cross-environment access

Environment context must be explicitly specified in each tool call; no implicit environment inheritance

SDK client initialization per environment adds memory overhead and startup latency

What makes it unique

vs alternatives

Enables cross-environment flag comparison within a single agent workflow vs. requiring separate API calls or manual environment switching

user targeting and segment evaluation

Medium confidence

Solves for

Best for

Personalization engines that need flag-driven user experiences

A/B testing workflows where agents need to know user assignment

User segmentation systems integrated with feature flags

Requires

LaunchDarkly SDK with user context support

User attributes pre-configured in LaunchDarkly project

User ID or identifying information available to agent

Limitations

User attributes must be pre-defined in LaunchDarkly; agents cannot dynamically create new attribute types

Segment membership is evaluated server-side; agents cannot directly query segment definitions

Custom attribute values are limited to LaunchDarkly's supported types (string, number, boolean, array) — complex objects not supported

What makes it unique

vs alternatives

Provides user-aware flag evaluation vs. generic flag queries, enabling agents to personalize behavior based on LaunchDarkly's targeting rules

flag analytics and audit trail access

Medium confidence

Solves for

Best for

Governance and compliance workflows that need flag audit trails

Analytics-driven agents that optimize rollouts based on usage metrics

Teams implementing flag lifecycle management with historical tracking

Requires

LaunchDarkly account with analytics/audit API access

LaunchDarkly SDK or API key with read permissions

MCP client capable of handling time-series or historical data

Limitations

Analytics data may be delayed by 5-15 minutes depending on LaunchDarkly's data pipeline

Audit logs are limited to recent changes (typically 90 days retention) — no long-term historical analysis

Variation distribution metrics are aggregated; no per-user variation tracking for privacy reasons

What makes it unique

vs alternatives

Allows agents to access flag analytics and audit trails vs. requiring manual dashboard inspection or separate analytics API integration

flag variation schema and metadata inspection

Medium confidence

Solves for

Best for

Agents that need to dynamically discover and adapt to flag configurations

Self-service flag management interfaces that expose flag metadata

Development workflows where agents need to understand flag structure

Requires

LaunchDarkly SDK with flag metadata access

API key with read permissions

MCP client capable of handling nested JSON structures

Limitations

Flag metadata is static at query time; changes require re-fetching

No schema validation for custom variation types — agents must interpret variation structure

Targeting rule details may be complex; agents cannot easily understand rule logic from metadata alone

What makes it unique

vs alternatives

Allows agents to introspect flag configurations vs. requiring hardcoded flag knowledge or manual documentation lookup

mcp server lifecycle and configuration management

Medium confidence

Solves for

Best for

DevOps teams deploying MCP servers for LaunchDarkly integration

Developers integrating the MCP server into Claude Desktop or other MCP clients

Teams managing multiple LaunchDarkly projects with different server instances

Requires

Node.js 16+ (or compatible JavaScript runtime)

LaunchDarkly SDK for Node.js

MCP server library (@modelcontextprotocol/sdk)

Limitations

Configuration is static at server startup; runtime configuration changes require restart

No built-in credential rotation — credentials must be manually updated and server restarted

Environment variables are the primary configuration method; no dynamic configuration API

What makes it unique

vs alternatives

Provides out-of-the-box MCP server setup for LaunchDarkly vs. requiring custom MCP server implementation

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

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@launchdarkly/mcp-server

Capabilities7 decomposed

feature flag state querying via mcp tools

feature flag crud operations via mcp resources

environment-aware flag evaluation context

user targeting and segment evaluation

flag analytics and audit trail access

flag variation schema and metadata inspection

mcp server lifecycle and configuration management

Related Artifactssharing capabilities

GrowthBook

InstantDB

open-terminal

label-studio

Supabase MCP Server

Label Studio

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @launchdarkly/mcp-server

Are you the builder of @launchdarkly/mcp-server?

Get the weekly brief

Data Sources

@launchdarkly/mcp-server

Capabilities7 decomposed

feature flag state querying via mcp tools

feature flag crud operations via mcp resources

environment-aware flag evaluation context

user targeting and segment evaluation

flag analytics and audit trail access

flag variation schema and metadata inspection

mcp server lifecycle and configuration management

Related Artifactssharing capabilities

GrowthBook

InstantDB

open-terminal

label-studio

Supabase MCP Server

Label Studio

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to @launchdarkly/mcp-server

Are you the builder of @launchdarkly/mcp-server?

Get the weekly brief

Data Sources