Davinci MCP Server
A Model Context Protocol (MCP) server for PingOne DaVinci
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DaVinci MCP Server
A Model Context Protocol (MCP) server that provides AI assistants with seamless access to PingOne's DaVinci identity orchestration platform resources. This server enables AI models to interact with DaVinci flows, applications, connectors, variables, and forms through a standardized interface.
[!WARNING] SECURITY & LEAST PRIVILEGE: This server grants an AI model significant access to your DaVinci environment configuration. All data returned from tools may be sent to the LLM provider.
- Use ONLY with trusted MCP clients.
- Follow the Principle of Least Privilege: Ensure the authenticating user is assigned a role with the minimum necessary permissions (e.g.,
DaVinci Admin Read Only).- HUMAN REVIEW REQUIRED: Always review all AI-generated configurations or insights before applying them to a live environment.
Overview
DaVinci is PingOne's no-code identity orchestration platform that allows organizations to build sophisticated identity and access management workflows. This MCP server acts as a bridge between MCP-compatible AI assistants and the DaVinci API, enabling:
- Flow Management: List and inspect identity orchestration flows and their versions.
- Flow Validation: Check flow configuration errors and deployment readiness.
- Flow Execution Monitoring: Monitor flow executions, review execution history, and troubleshoot failures.
- Application Configuration: Access application settings and flow policies.
- Connector Management: View available connectors and their configurations.
- Variable Management: Manage flow variables and their values.
- Form Management: Access form definitions and configurations.
- Connector Instances: Manage connector instance configurations.
Features
Available Tools
The server provides the following MCP tools organized into two collections:
Collection: davinci_admin
Core administrative tools for managing DaVinci resources (applications, flows, connectors, variables, forms).
Application Tools
| Tool | Description |
|---|---|
list_applications | Returns a list of all DaVinci applications. |
describe_application | Returns details of a single DaVinci application by ID. |
list_application_flow_policies | Returns all flow policies for a DaVinci application. |
describe_application_flow_policy | Returns details of a single flow policy for a DaVinci application. |
Flow Tools
| Tool | Description |
|---|---|
list_flows | Returns a list of all DaVinci flows. Supports attributes to project the response to specific top-level fields. Flow type is derived from the trigger field: no trigger = standard flow; trigger.type AUTHENTICATION = PingOne flow; trigger.type AUTHENTICATION + trigger.subtype CIBA = CIBA flow; trigger.type SCHEDULE = scheduled flow; trigger.type BATCH_PROCESSING_SUBFLOW = batch processing subflow. readOnly: true means the flow is read-only. |
describe_flow | Returns the complete definition of a DaVinci flow including the full node graph, edges, and settings. Use when auditing or understanding a flow's internal logic. Supports attributes to project the response to specific top-level fields and expand to include related fields inline (e.g. "dvlinterDetails"). |
list_flow_versions | Returns all versions of a specific DaVinci flow. |
describe_flow_version | Returns the complete definition of a specific DaVinci flow version, including the full node graph, edges, settings, and trigger configuration. Supports expand to include related fields inline (e.g. skcomponents). |
Connector Tools
| Tool | Description |
|---|---|
list_connectors | Returns a list of all available DaVinci connector types from the catalog. |
describe_connector | Returns the full details of a single DaVinci connector type by ID, including metadata, capabilities, configurable properties, and required credentials. |
list_connector_instances | Returns a list of all deployed DaVinci connector instances. |
describe_connector_instance | Returns details of a single deployed DaVinci connector instance by ID. |
Variable Tools
| Tool | Description |
|---|---|
list_variables | Returns a list of all DaVinci variables. Supports limit (1–50), cursor for pagination, and a SCIM filter to narrow results. |
describe_variable | Returns details of a single DaVinci variable by ID. |
Form Tools
| Tool | Description |
|---|---|
list_forms | Returns a list of all DaVinci forms. Use for discovery and finding form IDs. Use describe_form for field-level details. Supports a SCIM filter on category (eq). |
describe_form | Returns full configuration of a single DaVinci form including fields and layout. |
Collection: davinci_flow_troubleshooting
Specialized tools for flow validation, execution monitoring, and debugging.
Flow Troubleshooting Tools
| Tool | Description |
|---|---|
validate_flow | Validates a DaVinci flow configuration using the DVLinter validation engine. Use this tool to check deployment readiness, identify configuration errors and warnings (best-practice violations), and troubleshoot flow issues. Analyzes nodes (connectors and capabilities), connections (connector instances), node properties, and overall structure. Returns validation results including error counts or warning counts, and specific issue descriptions. Error locations: (1) linterError property within each node in graphData.elements.nodes for node specific issues (2) allLinterErrors property in graphData for all flow-level errors and warnings. Zero errors indicates deployment-ready status. This is a read-only operation that does not modify the flow. |
list_flow_executions | Returns a list of all executions for a specific DaVinci flow. Use this tool to find execution IDs for troubleshooting, debugging, or monitoring flow executions. Supports limit (max 500) and cursor for pagination and SCIM filter on timestamp (ge, le) with ISO 8601 dates, transactionId (eq) for specific transaction details. |
summarize_flow_execution | Returns detailed information about a specific DaVinci flow execution with status (success/failure), timestamps, input/output data, errors with stack traces, and user context. Use this tool to debug failures, summarize flow execution results, analyze execution behavior, verify data transformations, or investigate user-specific issues. Supports limit (max 500) and cursor for pagination and SCIM filter on timestamp (ge, le) with ISO 8601 dates. |
Authentication
The server uses OAuth 2.0 Authorization Code flow with PKCE for secure authentication:
- Automatic Token Management: Secure token storage using the system keychain (via
keytar). - Interactive Login: Interactive browser-based authentication flow.
- Regional Support: Support for different PingOne regional domains.
Prerequisites
- Node.js: Version 22.0.0 or higher. (Download & Install)
- PingOne Subscription: A licensed or trial PingOne cloud subscription.
- If you don't have one, you can sign up for a free trial.
- DaVinci Enabled: Ensure the DaVinci service is added to your environment.
- In the PingOne Admin Console, navigate to Environments > Your Environment > Services and ensure DaVinci is listed and active.
- Worker Application: A PingOne Worker Application in the same environment (see Setup for details).
- User Permissions: The authenticating user must be created in the environment if not present, and the user must have an appropriate role, such as DaVinci Admin Read Only.
Setup
1. PingOne Worker Application Setup
The MCP server requires a Worker Application to authenticate with the PingOne API.
- Access PingOne Admin: Log in to your PingOne Admin Console.
- Select Environment: Choose the environment where DaVinci is enabled.
- Navigate to Applications: Click Applications > Applications in the left navigation menu.
- Create Application:
- Click + Add Application and select Worker.
- Name: e.g.,
DaVinci MCP Server. - Description: Optional.
- Click Save.
- Enable the Worker application by toggling the button on top right.
- Configure Grant Types:
- Select the Configuration tab of your new application.
- Click the Edit (pencil) icon.
- Under Grant Types, ensure Authorization Code is selected.
- Under Response Type ensure Code is selected.
- PKCE Enforcement: Set to S256_REQUIRED.
- Redirect URIs: Add
http://127.0.0.1:7474/callback. - Token Endpoint Authentication Method: Set to None (Public Client).
- Click Save.
- Capture Credentials:
- Copy the Client ID from the Configuration tab. You will need this for the
AUTHORIZATION_CODE_CLIENT_IDvariable. - Note your Environment ID (found in the URL or the environment settings).
- Copy the Client ID from the Configuration tab. You will need this for the
2. User Setup & Role Assignment
The authenticating user must have the necessary permissions to access DaVinci resources.
- Navigate to Users: In the PingOne Admin Console, click Directory > Users.
- Create/Select User: Either create a new user (+ Add User) or select an existing one that you will use to log in via the MCP server.
- Assign Role:
- On the user's profile, navigate to the Roles tab.
- Click Grant Roles.
- Search for and select the DaVinci Admin Read Only role.
- Click Save.
3. Configure Environment Variables
The server requires the following environment variables. These should be configured in your MCP client's settings (see Usage below).
| Variable | Description | Example |
|---|---|---|
DAVINCI_MCP_ENVIRONMENT_ID | The ID of your PingOne environment. | a1b2c3d4-e5f6-g7h8-i9j0-k1l2m3n4o5p6 |
AUTHORIZATION_CODE_CLIENT_ID | The Client ID of your PingOne Worker Application. | your-client-id |
ROOT_DOMAIN | The regional PingOne domain. | pingone.com (NA), pingone.eu (EU), pingone.asia (APAC) |
CUSTOM_DOMAIN | (Optional) Your custom PingOne domain. | auth.example.com |
Usage
Quick Install
VS Code
Cursor
MCP Client Configuration
Replace your-environment-id and your-client-id with your actual PingOne environment ID and OAuth Client ID in the examples below.
Claude Desktop
Add the following to your claude_desktop_config.json:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"davinci": {
"command": "npx",
"args": ["-y", "@ping-identity/davinci-mcp-server", "start"],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
Claude Code (CLI)
Run the following command in your terminal:
claude mcp add --transport stdio davinci \
--env DAVINCI_MCP_ENVIRONMENT_ID="your-environment-id" \
--env AUTHORIZATION_CODE_CLIENT_ID="your-client-id" \
--env ROOT_DOMAIN="pingone.com" \
-- npx -y @ping-identity/davinci-mcp-server start
VS Code (Cline)
- Open the Cline sidebar in VS Code.
- Click the Settings (gear) icon.
- Scroll to MCP Servers and click Add MCP Server.
- Use the following configuration:
{
"davinci": {
"command": "npx",
"args": ["-y", "@ping-identity/davinci-mcp-server", "start"],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
Cursor
- Open Cursor Settings -> Features -> MCP.
- Click + Add New MCP Server.
- Name:
davinci - Type:
command - Command:
npx -y @ping-identity/davinci-mcp-server start
- Add environment variables:
DAVINCI_MCP_ENVIRONMENT_ID:your-environment-idAUTHORIZATION_CODE_CLIENT_ID:your-client-idROOT_DOMAIN:pingone.com
Gemini CLI
Add the following to your ~/.gemini/settings.json:
{
"mcpServers": {
"davinci": {
"command": "npx",
"args": ["-y", "@ping-identity/davinci-mcp-server", "start"],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
CLI Commands & Flags
The server requires a command to execute and supports several flags to customize its behavior. These should be added to the args array in your MCP client configuration:
Commands
start: Initiates the MCP server (required for normal operation).
Options
--include-collections <list>: Comma-separated list of collection names to include (e.g.,davinci_admin,davinci_flow_troubleshooting).--exclude-collections <list>: Comma-separated list of collection names to exclude.--include-tools <list>: Comma-separated list of tool names to include.--exclude-tools <list>: Comma-separated list of tool names to exclude.--verbose: Enable verbose logging to stderr.--logout: Trigger a logout flow on startup by clearing stored tokens.--help: Show the help message.
MCP Configuration Examples
These examples show how to configure claude_desktop_config.json for different scenarios. Change accordingly for other providers
1. Basic Server Startup
The standard configuration to run the server with all default tools enabled.{
"mcpServers": {
"davinci": {
"command": "npx",
"args": ["-y", "@ping-identity/davinci-mcp-server", "start"],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
2. Filter by Tool Collection
Limit the tools exposed to Claude to only those in the `davinci_admin` collection.{
"mcpServers": {
"davinci": {
"command": "npx",
"args": [
"-y",
"@ping-identity/davinci-mcp-server",
"start",
"--include-collections",
"davinci_admin"
],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
2a. Include Flow Troubleshooting Tools Only
Expose only the flow troubleshooting and debugging tools.{
"mcpServers": {
"davinci": {
"command": "npx",
"args": [
"-y",
"@ping-identity/davinci-mcp-server",
"start",
"--include-collections",
"davinci_flow_troubleshooting"
],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
3. Filter by Specific Tools
Expose only a surgical set of tools (e.g., only flows) to the AI assistant.{
"mcpServers": {
"davinci": {
"command": "npx",
"args": [
"-y",
"@ping-identity/davinci-mcp-server",
"start",
"--include-tools",
"list_flows,describe_flow"
],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
4. Exclude Specific Tools
Enable all tools except for those related to variables.{
"mcpServers": {
"davinci": {
"command": "npx",
"args": [
"-y",
"@ping-identity/davinci-mcp-server",
"start",
"--exclude-tools",
"describe_variable,list_variables"
],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
5. Enable Verbose Logging
Enable detailed logging to help debug connection or tool execution issues.{
"mcpServers": {
"davinci": {
"command": "npx",
"args": ["-y", "@ping-identity/davinci-mcp-server", "start", "--verbose"],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
Maintenance & Utility Commands
These commands are intended to be run manually in your terminal for maintenance or discovery.
1. Logout & Clear Credentials
Force the server to clear stored tokens from the system keychain. This is useful if you need to switch users or re-authenticate.npx -y @ping-identity/davinci-mcp-server start --logout
2. Display Help
View all available commands, options, and required environment variables directly in your terminal.npx -y @ping-identity/davinci-mcp-server --help
Example (Claude Desktop Configuration):
{
"mcpServers": {
"davinci": {
"command": "npx",
"args": [
"-y",
"@ping-identity/davinci-mcp-server",
"start",
"--include-tools",
"list_flows,describe_flow",
"--verbose"
],
"env": {
"DAVINCI_MCP_ENVIRONMENT_ID": "your-environment-id",
"AUTHORIZATION_CODE_CLIENT_ID": "your-client-id",
"ROOT_DOMAIN": "pingone.com"
}
}
}
}
Development
1. Installation
git clone https://github.com/pingidentity/davinci-mcp-server.git
cd davinci-mcp-server
npm ci
2. Available Scripts
npm run dev: Watch mode for development.npm run build: Build the project.npm run typecheck: Run TypeScript type checking.npm run lint: Run ESLint.npm run format: Format code with Prettier.npm run test: Run tests using Vitest.npm run inspect: Run with MCP Inspector for debugging.
Troubleshooting
- Port Conflict: The authentication callback server uses port
7474. Ensure this port is available. - Keychain Access: On Linux, ensure
libsecretis installed forkeytarto function. On macOS/Windows, it uses the native keychain. - Authentication Timeout: The browser login must be completed within 5 minutes.
- Invalid Tokens: Use the
--logoutflag to clear corrupted or invalid tokens from the keychain.
License
This project is licensed under the Apache-2.0 License.
