> ## Documentation Index
> Fetch the complete documentation index at: https://confidence.spotify.com/llms.txt
> Use this file to discover all available pages before exploring further.

# MCP Servers

> Confidence MCP servers give AI assistants access to documentation, feature flag management, and experiment analysis tools.

Confidence has three MCP servers:

* **Documentation MCP**: Search and retrieve Confidence documentation
* **Flags MCP**: Create and manage feature flags
* **Experiments MCP**: Explore and analyze experiments and their results

## Documentation MCP Server

The Documentation MCP provides AI assistants with access to Confidence documentation through semantic search, regular expression search, and SDK integration guides.

### Integration Setup

**No authentication required** for the Documentation MCP server. The server uses streamable HTTP as the transport and the URL is `https://mcp.confidence.dev/mcp/docs`.

<Tabs>
  <Tab title="Claude Code">
    ```bash theme={null}
    claude mcp add --transport http confidence-docs https://mcp.confidence.dev/mcp/docs
    ```
  </Tab>

  <Tab title="Cursor">
    <Steps>
      <Step title="Open the Command Palette">
        Use `Command + Shift + P` (`Ctrl + Shift + P` on Windows) and search for `Open MCP settings`.
      </Step>

      <Step title="Add the server">
        Select **New MCP Server** and add the following to the `mcpServers` JSON:

        ```json theme={null}
        "confidence-docs": "https://mcp.confidence.dev/mcp/docs"
        ```
      </Step>
    </Steps>
  </Tab>

  <Tab title="VS Code">
    <Steps>
      <Step title="Create the .vscode directory">
        Create a `.vscode` directory in your workspace root if it doesn't exist.
      </Step>

      <Step title="Create mcp.json">
        Create a file named `mcp.json` in the `.vscode` directory.
      </Step>

      <Step title="Add the server configuration">
        Add the `confidence-docs` server to your configuration:

        ```json theme={null}
        {
          "servers": {
            "confidence-docs": { "url": "https://mcp.confidence.dev/mcp/docs" }
          }
        }
        ```
      </Step>

      <Step title="Start the server">
        Click `Start` next to the MCP server name in the JSON file to start it.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### Available Tools

#### searchDocumentation

Searches the Confidence documentation using semantic search to learn about experiments, A/B tests, rollouts, feature flags, metrics, surfaces, insights, and other experiment-related topics. Returns the 10 most relevant chunks using Maximum Marginal Relevance (MMR) to balance relevance and diversity.

#### getFullSource

Retrieves the full text content from a specific Confidence documentation source URL.

#### grepDocumentation

Searches the Confidence documentation content using regular expressions. Returns a list of documentation pages that contain matches for the given regular expression pattern.

#### getCodeSnippetAndSdkIntegrationTips

Gets complete integration guides with code examples and README documentation for integrating Confidence feature flags. Returns full integration examples including OpenFeature provider setup, best practices, and configuration for the specified SDK.

### Example Usage

Once integrated, ask your AI assistant to:

* "Search Confidence documentation for information about A/B testing"
* "Show how to integrate Confidence with Python"
* "Summarize the A/B test quickstart"

## Flag Management MCP Server

The Flag Management MCP provides AI assistants with tools to manage Confidence feature flags, including creation, modification, targeting rules, and testing.

### Integration Setup

The Confidence Flags MCP **requires authentication**. Allow access from your IDE or developer tool where you use the MCP server. The server uses streamable HTTP as the transport and the URL is `https://mcp.confidence.dev/mcp/flags`.

<Tabs>
  <Tab title="Claude Code">
    ```bash theme={null}
    claude mcp add --transport http confidence-flags https://mcp.confidence.dev/mcp/flags
    ```

    After adding, open Claude Code, run `/mcp` and select `confidence-flags` to authenticate.
  </Tab>

  <Tab title="Cursor">
    <Steps>
      <Step title="Open the Command Palette">
        Use `Command + Shift + P` (`Ctrl + Shift + P` on Windows) and search for `Open MCP settings`.
      </Step>

      <Step title="Add the server">
        Select **New MCP Server** and add the following to the `mcpServers` JSON:

        ```json theme={null}
        "confidence-flags": "https://mcp.confidence.dev/mcp/flags"
        ```
      </Step>

      <Step title="Authenticate">
        Click `Connect` to authenticate.
      </Step>
    </Steps>
  </Tab>

  <Tab title="VS Code">
    <Steps>
      <Step title="Create the .vscode directory">
        Create a `.vscode` directory in your workspace root if it doesn't exist.
      </Step>

      <Step title="Create mcp.json">
        Create a file named `mcp.json` in the `.vscode` directory.
      </Step>

      <Step title="Add the server configuration">
        Add the `confidence-flags` server to your configuration:

        ```json theme={null}
        {
          "servers": {
            "confidence-flags": { "url": "https://mcp.confidence.dev/mcp/flags" }
          }
        }
        ```
      </Step>

      <Step title="Start and authenticate">
        Click `Start` next to the MCP server name in the JSON file and authenticate when prompted.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### Available Tools

#### listClients

Lists all available Confidence clients for flag operations.

#### listFlags

Lists all active feature flags with summary information including names, schemas, and variants.

#### getFlag

Retrieves detailed information about a specific feature flag, including its complete schema, variants, and targeting rules.

#### createFlag

Creates a new feature flag with schema and variant definitions.

#### addFlagVariant

Adds a new variant to an existing feature flag.

#### updateFlagSchema

Updates the schema definition of an existing feature flag.

#### createOverrideRule

Creates targeting rules to override flag behavior for specific entities.

#### testResolveFlag

Tests flag resolution for specific clients and entities and explains why the system selects a particular variant.

#### analyzeFlagUsage

Finds unused Confidence feature flags or flags fully rolled out, helping you clean up feature flag code.

### Example Usage

Once integrated, ask your AI assistant to:

* "List all feature flags in Confidence"
* "Create a new flag called 'new-checkout-flow' with a boolean schema"
* "Add a variant to the 'new-checkout-flow' flag"
* "Create an individual targeting rule for user 'test-user' to see the 'variant-b' of 'experiment-flag'"
* "Test flag resolution for 'new-checkout-flow' with user '[john@example.com](mailto:john@example.com)'"
* "Analyze what flags you can clean up in this codebase"

## Experiments MCP Server

The Experiments MCP provides AI assistants with tools to explore and analyze Confidence experiments, including A/B tests and rollouts.

### Integration Setup

The Confidence Experiments MCP **requires authentication**. Allow access from your IDE or developer tool where you use the MCP server. The server uses streamable HTTP as the transport and the URL is `https://mcp.confidence.dev/mcp/experiments`.

<Tabs>
  <Tab title="Claude Code">
    ```bash theme={null}
    claude mcp add --transport http confidence-experiments https://mcp.confidence.dev/mcp/experiments
    ```

    After adding, open Claude Code, run `/mcp` and select `confidence-experiments` to authenticate.
  </Tab>

  <Tab title="Cursor">
    <Steps>
      <Step title="Open the Command Palette">
        Use `Command + Shift + P` (`Ctrl + Shift + P` on Windows) and search for `Open MCP settings`.
      </Step>

      <Step title="Add the server">
        Select **New MCP Server** and add the following to the `mcpServers` JSON:

        ```json theme={null}
        "confidence-experiments": "https://mcp.confidence.dev/mcp/experiments"
        ```
      </Step>

      <Step title="Authenticate">
        Click `Connect` to authenticate.
      </Step>
    </Steps>
  </Tab>

  <Tab title="VS Code">
    <Steps>
      <Step title="Create the .vscode directory">
        Create a `.vscode` directory in your workspace root if it doesn't exist.
      </Step>

      <Step title="Create mcp.json">
        Create a file named `mcp.json` in the `.vscode` directory.
      </Step>

      <Step title="Add the server configuration">
        Add the `confidence-experiments` server to your configuration:

        ```json theme={null}
        {
          "servers": {
            "confidence-experiments": { "url": "https://mcp.confidence.dev/mcp/experiments" }
          }
        }
        ```
      </Step>

      <Step title="Start and authenticate">
        Click `Start` next to the MCP server name in the JSON file and authenticate when prompted.
      </Step>
    </Steps>
  </Tab>
</Tabs>

### Available Tools

{/*vale Confidence.Spelling = NO*/}

#### list\_experiments

Lists Confidence experiments (A/B tests and rollouts). Returns experiment names, display names, states, owners, and creation times. Supports two modes:

* **List mode** (default): Use the `filter` parameter with `Lucene` query syntax (for example, `state:live` for running experiments) and `orderBy` to sort results.
* **Search mode**: Provide a `query` parameter for full-text search. In search mode, results order by relevance and the `filter` and `orderBy` parameters have no effect.

You can infer the experiment type from the resource name (for example, `workflows/abtest/...` or `workflows/rollout/...`).

#### get\_experiment

Retrieves detailed information about a specific experiment. By default, returns a compact summary with key fields:

* Name, state, owner, and creation time
* Metrics with types, minimum detectable effect (MDE), and non-inferiority margin (NIM)
* Decision outcome (for ended A/B tests)
* Available analysis result names

Set `summary=false` for full details including configuration, checks, stats, and state history.

#### get\_results

Retrieves statistical analysis results for an experiment. By default, returns a summary with:

* Relative effect estimates and confidence intervals
* Significance status and status messages
* Sample sizes per treatment
* Shipping recommendations per treatment

Accepts either an experiment instance name (for example, `workflows/abtest/instances/{id}`) or a specific analysis result name. When given an instance name, the tool automatically resolves the primary analysis result.

Set `summary=false` for the full detailed output.

#### get\_resource

Looks up details of Confidence resources referenced in experiment data. Supports:

* `metrics/*` - Metric definitions
* `entities/*` - Entity definitions
* `surfaces/*` - Surface configurations
* `segments/*` - Segment definitions
* `factTables/*` - Fact table definitions
* `flags/*` - Feature flag configurations
* `identities/*` - User identities
* `assignmentTables/*` - Assignment table definitions
* `clients/*` - Client configurations

{/*vale Confidence.TitleCaseHeadings = YES*/}

### Example Usage

Once integrated, ask your AI assistant to:

* "List all running experiments"
* "Search for experiments related to checkout"
* "Show me details about the homepage-redesign experiment"
* "Get the results for the checkout-flow A/B test"
* "What's the status of the metrics in my onboarding rollout?"