ref-mcp-cli
MCP ServerFreeModelContextProtocol server for Ref
Capabilities5 decomposed
modelcontextprotocol server instantiation and lifecycle management
Medium confidenceProvides a CLI-based MCP server that implements the ModelContextProtocol specification, handling server initialization, request routing, and connection lifecycle management. The server exposes Ref capabilities through the MCP transport layer, allowing clients (Claude, IDEs, agents) to discover and invoke Ref tools via standardized MCP message protocols. Implements request/response serialization and error handling within the MCP framework.
Wraps Ref functionality as a first-class MCP server, enabling protocol-level integration with Claude and other MCP clients rather than requiring custom API wrappers or direct library imports
Provides standardized MCP transport for Ref tools, avoiding the need for custom REST APIs or SDK bindings while maintaining compatibility with the broader MCP ecosystem
ref tool discovery and schema exposition via mcp
Medium confidenceAutomatically discovers available Ref tools and exposes their schemas (parameters, return types, descriptions) through MCP's tools list endpoint. Clients can query the server to enumerate all available Ref capabilities, their input/output contracts, and documentation. Schema exposition follows MCP's JSON Schema format for parameter validation and IDE autocomplete support.
Leverages MCP's standardized tools/list protocol to expose Ref's tool catalog with full JSON Schema validation, enabling clients to validate parameters before invocation and provide IDE-level autocomplete
Eliminates manual tool registration in MCP clients by auto-discovering Ref tools; more maintainable than hardcoded tool lists that drift from actual Ref capabilities
ref tool invocation through mcp call routing
Medium confidenceRoutes MCP tool call requests to the underlying Ref implementation, marshaling parameters from MCP format into Ref's expected input structure and serializing results back to MCP response format. Implements error handling and result transformation to ensure Ref tool outputs are properly formatted as MCP text or resource responses. Supports both synchronous tool execution and streaming results where applicable.
Implements MCP's tools/call protocol as a direct passthrough to Ref's execution engine, preserving Ref's native error handling and output semantics while adapting to MCP's request/response envelope
Provides transparent tool invocation without wrapping Ref's logic in additional abstraction layers, reducing latency and maintaining compatibility with Ref's native behavior
cli-based server configuration and startup
Medium confidenceExposes command-line arguments to configure the MCP server's behavior, including port binding, logging level, authentication tokens, and Ref-specific settings. The CLI parses arguments, initializes the MCP server with the specified configuration, and manages the server lifecycle (startup, shutdown, signal handling). Supports environment variable overrides for containerized or CI/CD deployments.
Provides a minimal CLI interface for server configuration, relying on standard Node.js conventions (environment variables, process signals) rather than custom config file formats
Simpler than configuration-file-based servers for containerized deployments; easier to integrate with Docker and Kubernetes environment variable patterns
mcp protocol compliance and version negotiation
Medium confidenceImplements the ModelContextProtocol specification, including protocol version negotiation with clients, capability advertisement, and message format validation. The server declares its supported MCP version and features during the initialization handshake, allowing clients to adapt their behavior. Validates incoming MCP messages for correctness and rejects malformed requests with appropriate error codes.
Implements strict MCP protocol compliance with version negotiation, ensuring interoperability with diverse MCP clients while rejecting non-compliant messages early
Provides protocol-level safety guarantees that prevent silent failures from version mismatches or malformed messages, compared to lenient servers that may accept invalid requests
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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AgentQL
** - Enable AI agents to get structured data from unstructured web with [AgentQL](https://www.agentql.com/).
Best For
- ✓developers building MCP-compatible AI agents or IDE extensions
- ✓teams standardizing on ModelContextProtocol for tool integration
- ✓Claude users wanting to add Ref capabilities to their conversations
- ✓MCP client developers building UI for tool discovery
- ✓Claude users wanting dynamic tool availability
- ✓IDE extension developers integrating Ref via MCP
- ✓Claude users executing Ref operations via MCP
- ✓AI agents using Ref as a tool in their action loops
Known Limitations
- ⚠MCP protocol overhead adds latency compared to direct library calls
- ⚠Requires MCP client support — not compatible with non-MCP tools
- ⚠Server must be running as a separate process, adding operational complexity
- ⚠Schema exposition is static at server startup — dynamic tool registration requires server restart
- ⚠Complex Ref tool schemas may not map perfectly to JSON Schema constraints
- ⚠No built-in caching of schema metadata — each discovery request re-queries the server
Requirements
Input / Output
UnfragileRank
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ModelContextProtocol server for Ref
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