Camel MCP Server

Since Camel 4.6, the recommended approach for building REST APIs from OpenAPI specifications is contract-first: referencing the OpenAPI spec directly at runtime via rest:openApi rather than generating REST DSL code. These tools help validate, scaffold, and provide mock guidance for that workflow.

Add the following to your project’s .mcp.json (or ~/.claude/mcp.json for global configuration):

Add the server to your MCP configuration:

Configure MCP servers in your .vscode/mcp.json or in the user settings:

JetBrains IDEs support MCP servers starting from 2025.1. Configure them in Settings > Tools > AI Assistant > MCP Servers, or create an .junie/mcp.json file in your project root:

Any MCP client that supports the STDIO transport can launch the server directly:

To start the server with the HTTP/SSE transport enabled:

MCP clients that support HTTP/SSE can then connect to the server at http://localhost:8080/mcp/sse.

Prompt your AI assistant with:

The assistant calls camel_catalog_components with label=messaging and receives structured results with name, title, description, label, deprecation status, and support level for each matching component.

The assistant calls camel_catalog_component_doc with component=kafka and receives the full component model including the URI syntax, Maven coordinates, and every endpoint option with types, defaults, and descriptions.

The assistant calls camel_catalog_kamelets with type=source and filter=aws and returns matching Kamelets with their name, type, support level, and description.

To drill into a specific Kamelet:

The assistant calls camel_catalog_kamelet_doc with kamelet=aws-s3-source and returns the complete property list including required fields, types, defaults, and Maven dependencies.

The assistant calls camel_validate_route and detects the typo (brkers), reports the URI as invalid, and suggests the correct option name (brokers).

The assistant calls camel_validate_yaml_dsl which validates the route against the Camel YAML DSL JSON schema and reports that setCheese is not a valid DSL element, returning the instance path and error type so the AI can suggest the correct processor name (e.g., setBody).

Paste a route and ask:

The assistant calls camel_route_context which extracts all components and EIPs used in the route, looks up their documentation from the catalog, and returns enriched context so the AI can provide an accurate explanation.

The assistant calls camel_route_harden_context which analyzes the route for security-sensitive components, detects issues (hardcoded credentials, HTTP instead of HTTPS, plain FTP, etc.), assigns risk levels, and returns structured findings with remediation recommendations.

Paste a stack trace or error message and ask:

The assistant calls camel_error_diagnose which identifies all three exceptions in the chain, extracts the kafka component, and returns common causes (missing camel-kafka dependency, typo in URI scheme), suggested fixes (add the dependency, verify the URI), and links to the relevant Camel documentation.

Provide your pom.xml and route content, and the assistant calls camel_dependency_check. It detects whether your Camel version is outdated compared to the latest release, identifies components used in the route that are missing from the pom (e.g., camel-kafka for kafka: endpoints), and flags version conflicts where a dependency has an explicit version override while a BOM is present. Each issue comes with a corrected Maven snippet you can paste directly into your pom.

The assistant calls camel_version_list with runtime=spring-boot and lts=true and returns version information including release dates, end-of-life dates, and JDK requirements.

Start by providing your project’s pom.xml:

The assistant calls camel_migration_analyze to detect the runtime, current Camel version, Java version, and component dependencies. It then calls camel_migration_compatibility to check for breaking changes and camel_migration_recipes to provide the OpenRewrite commands for automated migration.

The assistant calls camel_migration_guide_search with query=direct-vm and returns matching snippets from the official migration guides with version info and URLs, so you can see exactly what changed and how to adapt.

The assistant calls camel_migration_wildfly_karaf which returns the Maven archetype command to create a new Quarkus-based project, migration steps, and relevant guide URLs. The archetype generates the correct project structure so you can then migrate your routes and source files into it.

Paste the OpenAPI spec (JSON or YAML) and the assistant calls camel_openapi_validate. It reports any compatibility issues such as missing operationId fields, unsupported security schemes (OAuth2, mutual TLS), OpenAPI 3.1 limitations, and webhooks usage. A valid spec with no issues returns valid: true with an operation count.

The assistant calls camel_openapi_scaffold with specFilename=petstore.yaml and missingOperation=mock. It returns a ready-to-use YAML file containing:

The assistant calls camel_openapi_mock_guidance with mode=mock. It returns:

For a complete prototyping workflow, you can combine all three tools:

The assistant first calls camel_openapi_validate to check for issues, then calls camel_openapi_scaffold to generate the route scaffold. This gives you a validated spec and a complete starting point where you can implement routes one at a time while Camel auto-mocks the rest.

In MCP clients that support prompts, select the camel_build_integration prompt and provide your requirements:

The prompt guides the assistant through a structured seven-step workflow: discovering the right components (kafka, aws2-s3), selecting EIPs (filter), retrieving their documentation, building a YAML route, validating it against the YAML DSL schema, and running a security review — all in the correct order.

Select the camel_migrate_project prompt and provide your project’s pom.xml:

The prompt orchestrates the full migration workflow: analyzing your project, checking component compatibility, retrieving OpenRewrite recipes, searching migration guides for per-component breaking changes, and producing a structured migration summary with blockers, manual steps, and the exact commands to run.

Select the camel_security_review prompt and provide a route:

The prompt guides the assistant through a security audit: analyzing the route for vulnerabilities and security-sensitive components, understanding the data flow, and producing a structured audit checklist with critical issues, warnings, positive findings, and actionable recommendations.