What can terry-mcp do?

terry cli command exposure via mcp protocol, mcp tool schema generation from cli interface, bidirectional stdio communication with mcp clients, terry cli command execution with output capture, mcp server lifecycle management

terry-mcp

MCP ServerFree

ModelContextProtocol server for Terry CLI integration

Open Source

/ 100

5 capabilities

Capabilities5 decomposed

terry cli command exposure via mcp protocol

Medium confidence

Exposes Terry CLI commands as MCP tools through a standardized Model Context Protocol server interface, enabling LLM clients to discover and invoke Terry operations without direct shell access. Implements MCP tool schema generation that maps CLI arguments to structured function parameters, allowing Claude and other MCP-compatible clients to call Terry commands with type-safe argument passing and response handling.

Solves for

Integrate Terry CLI workflows into Claude projects without shell executionEnable LLM agents to orchestrate Terry operations as part of multi-step reasoning chainsExpose Terry functionality to MCP-compatible clients for automated task execution

Best for

AI engineers building LLM agents that need to interact with Terry CLI

Teams using Claude with MCP servers for workflow automation

Developers migrating from direct shell execution to structured tool calling

Requires

Node.js 16+ (typical for npm packages)

Terry CLI installed and accessible in PATH

MCP-compatible client (Claude, or other MCP consumers)

Limitations

Requires Terry CLI to be installed and available in the system PATH

MCP protocol overhead adds latency compared to direct CLI invocation

No built-in retry logic or error recovery — relies on client-side handling

What makes it unique

Bridges Terry CLI (a specific domain tool) into the MCP ecosystem by wrapping CLI invocations as discoverable, schema-validated tools that LLM clients can call with structured parameters rather than raw shell commands

vs alternatives

Provides type-safe tool calling for Terry workflows compared to naive shell execution, while maintaining full compatibility with the MCP standard that Claude and other clients already support

mcp tool schema generation from cli interface

Medium confidence

Automatically generates MCP-compliant tool schemas by introspecting Terry CLI's command structure, argument definitions, and help text. Converts CLI flags, options, and positional arguments into JSON Schema definitions with proper type constraints, descriptions, and required field markers, enabling clients to validate inputs before execution and provide intelligent autocomplete.

Solves for

Automatically discover Terry CLI capabilities without manual schema definitionEnable IDE/client-side validation of Terry command arguments before sending to MCP serverGenerate human-readable tool descriptions from CLI help text for LLM context

Best for

MCP server developers wrapping existing CLI tools

Teams wanting to expose CLI tools to LLMs with minimal boilerplate

Automation platforms that need dynamic tool discovery

Requires

Terry CLI with standard --help output

Node.js JSON Schema support (built-in)

MCP server framework (likely included in terry-mcp)

Limitations

Schema generation accuracy depends on CLI help text quality and consistency

Complex nested subcommands may not map cleanly to flat MCP tool schemas

No support for dynamic arguments or context-dependent CLI behavior

What makes it unique

Implements CLI-to-schema mapping that extracts argument definitions from Terry's help output and converts them into JSON Schema with proper type inference, rather than requiring manual schema definition per command

vs alternatives

Reduces boilerplate compared to manually defining MCP tool schemas for each CLI command, while maintaining compatibility with standard JSON Schema validation that MCP clients expect

bidirectional stdio communication with mcp clients

Medium confidence

Implements the MCP server-side protocol handler using Node.js stdio streams, establishing bidirectional JSON-RPC communication with MCP clients (like Claude). Handles message framing, request routing, and response serialization according to the MCP specification, allowing clients to send tool invocation requests and receive results through standard input/output channels.

Solves for

Establish persistent MCP connection between Claude and Terry CLIRoute tool invocation requests from MCP clients to Terry CLI executionStream command output back to clients with proper error handling

Best for

Developers building MCP servers that wrap CLI tools

Teams integrating with Claude Desktop or other stdio-based MCP clients

Automation platforms using MCP for tool orchestration

Requires

Node.js with stdio stream support (all versions)

MCP client that supports stdio transport (Claude Desktop, etc.)

Proper process lifecycle management in parent application

Limitations

Stdio-based communication limits throughput for large binary outputs

No built-in connection pooling or multiplexing across multiple clients

Process-per-connection model may not scale for high-concurrency scenarios

What makes it unique

Implements MCP server protocol handling over Node.js stdio streams with proper JSON-RPC framing, enabling seamless integration with Claude Desktop and other MCP clients without requiring HTTP infrastructure

vs alternatives

Simpler deployment than HTTP-based MCP servers (no port management, firewall rules, or TLS certificates needed), while maintaining full MCP protocol compliance for client compatibility

terry cli command execution with output capture

Medium confidence

Executes Terry CLI commands as child processes and captures stdout/stderr output, returning results to MCP clients with proper exit code handling and error propagation. Uses Node.js child_process module to spawn Terry with arguments derived from MCP tool invocation parameters, managing process lifecycle and timeout behavior.

Solves for

Execute Terry operations triggered by LLM tool callsCapture and return command output to Claude for further reasoningHandle command failures and propagate errors back to MCP clients

Best for

LLM agents that need to execute Terry workflows as part of reasoning chains

Automation systems that orchestrate Terry commands through MCP

Teams building multi-step workflows combining LLM reasoning with Terry execution

Requires

Terry CLI installed and in PATH

Node.js child_process module (built-in)

Sufficient system resources for spawning child processes

Limitations

No built-in timeout enforcement — long-running Terry commands may block MCP client

Output size limits may apply if Terry produces large stdout/stderr

No streaming output support — entire command output buffered before returning

What makes it unique

Wraps Terry CLI execution in a child process with structured output capture and error handling, mapping MCP tool parameters directly to CLI arguments without shell interpretation

vs alternatives

Safer than shell execution (no injection vulnerabilities) and more reliable than direct library calls, while maintaining full compatibility with Terry's CLI interface

mcp server lifecycle management

Medium confidence

Manages the MCP server process lifecycle including initialization, client connection handling, and graceful shutdown. Implements proper signal handling for SIGTERM/SIGINT to clean up resources, manages the stdio transport connection, and ensures the server remains responsive to client requests throughout its lifetime.

Solves for

Keep MCP server running and responsive to Claude requestsHandle server shutdown cleanly without orphaning child processesManage connection state between MCP client and Terry CLI wrapper

Best for

Production deployments of MCP servers in Claude Desktop or other clients

Teams needing reliable long-running MCP server processes

Automation platforms that spawn and manage MCP server instances

Requires

Node.js event loop and signal handling (built-in)

Proper process management by parent application (systemd, supervisor, etc.)

Standard input/output streams available

Limitations

No built-in health checks or automatic restart on failure

Limited observability — no structured logging or metrics by default

Single-threaded event loop may block on slow Terry commands

What makes it unique

Implements MCP server lifecycle with proper signal handling and resource cleanup, ensuring the server can be safely started/stopped by parent applications like Claude Desktop without leaving orphaned processes

vs alternatives

More robust than naive process spawning by handling OS signals and cleanup, while remaining lightweight compared to full application servers

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

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Best For

✓AI engineers building LLM agents that need to interact with Terry CLI
✓Teams using Claude with MCP servers for workflow automation
✓Developers migrating from direct shell execution to structured tool calling
✓MCP server developers wrapping existing CLI tools
✓Teams wanting to expose CLI tools to LLMs with minimal boilerplate
✓Automation platforms that need dynamic tool discovery
✓Developers building MCP servers that wrap CLI tools
✓Teams integrating with Claude Desktop or other stdio-based MCP clients

Known Limitations

⚠Requires Terry CLI to be installed and available in the system PATH
⚠MCP protocol overhead adds latency compared to direct CLI invocation
⚠No built-in retry logic or error recovery — relies on client-side handling
⚠Limited to Terry's CLI interface — cannot access internal APIs directly
⚠Schema generation accuracy depends on CLI help text quality and consistency
⚠Complex nested subcommands may not map cleanly to flat MCP tool schemas

Requirements

Node.js 16+ (typical for npm packages)Terry CLI installed and accessible in PATHMCP-compatible client (Claude, or other MCP consumers)npm or yarn package managerTerry CLI with standard --help outputNode.js JSON Schema support (built-in)MCP server framework (likely included in terry-mcp)Node.js with stdio stream support (all versions)

Input / Output

Accepts: CLI argument strings, Structured JSON parameters mapped to CLI flags, CLI help text output, Terry command metadata, JSON-RPC messages over stdin, MCP protocol requests, MCP tool invocation with parameters, OS signals (SIGTERM, SIGINT), MCP client connection events

Produces: CLI stdout/stderr as text, Structured JSON responses (if Terry supports JSON output mode), JSON Schema objects, MCP tool definitions, JSON-RPC responses over stdout, MCP protocol responses, Command stdout as text, Command stderr as text, Exit code as integer, Process exit codes, Cleanup completion status

UnfragileRank

Adoption15%(30% weight)

Quality13%(25% weight)

Ecosystem30%(25% weight)

Match Graph10%(15% 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

5 capabilities

Visit terry-mcp→

Package Details

npm

Registry

0.3.0

Version

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ModelContextProtocol server for Terry CLI integration

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Capabilities5 decomposed

terry cli command exposure via mcp protocol

Medium confidence

Solves for

Best for

AI engineers building LLM agents that need to interact with Terry CLI

Teams using Claude with MCP servers for workflow automation

Developers migrating from direct shell execution to structured tool calling

Requires

Node.js 16+ (typical for npm packages)

Terry CLI installed and accessible in PATH

MCP-compatible client (Claude, or other MCP consumers)

Limitations

Requires Terry CLI to be installed and available in the system PATH

MCP protocol overhead adds latency compared to direct CLI invocation

No built-in retry logic or error recovery — relies on client-side handling

What makes it unique

vs alternatives

Provides type-safe tool calling for Terry workflows compared to naive shell execution, while maintaining full compatibility with the MCP standard that Claude and other clients already support

mcp tool schema generation from cli interface

Medium confidence

Solves for

Best for

MCP server developers wrapping existing CLI tools

Teams wanting to expose CLI tools to LLMs with minimal boilerplate

Automation platforms that need dynamic tool discovery

Requires

Terry CLI with standard --help output

Node.js JSON Schema support (built-in)

MCP server framework (likely included in terry-mcp)

Limitations

Schema generation accuracy depends on CLI help text quality and consistency

Complex nested subcommands may not map cleanly to flat MCP tool schemas

No support for dynamic arguments or context-dependent CLI behavior

What makes it unique

vs alternatives

Reduces boilerplate compared to manually defining MCP tool schemas for each CLI command, while maintaining compatibility with standard JSON Schema validation that MCP clients expect

bidirectional stdio communication with mcp clients

Medium confidence

Solves for

Establish persistent MCP connection between Claude and Terry CLIRoute tool invocation requests from MCP clients to Terry CLI executionStream command output back to clients with proper error handling

Best for

Developers building MCP servers that wrap CLI tools

Teams integrating with Claude Desktop or other stdio-based MCP clients

Automation platforms using MCP for tool orchestration

Requires

Node.js with stdio stream support (all versions)

MCP client that supports stdio transport (Claude Desktop, etc.)

Proper process lifecycle management in parent application

Limitations

Stdio-based communication limits throughput for large binary outputs

No built-in connection pooling or multiplexing across multiple clients

Process-per-connection model may not scale for high-concurrency scenarios

What makes it unique

vs alternatives

Simpler deployment than HTTP-based MCP servers (no port management, firewall rules, or TLS certificates needed), while maintaining full MCP protocol compliance for client compatibility

terry cli command execution with output capture

Medium confidence

Solves for

Execute Terry operations triggered by LLM tool callsCapture and return command output to Claude for further reasoningHandle command failures and propagate errors back to MCP clients

Best for

LLM agents that need to execute Terry workflows as part of reasoning chains

Automation systems that orchestrate Terry commands through MCP

Teams building multi-step workflows combining LLM reasoning with Terry execution

Requires

Terry CLI installed and in PATH

Node.js child_process module (built-in)

Sufficient system resources for spawning child processes

Limitations

No built-in timeout enforcement — long-running Terry commands may block MCP client

Output size limits may apply if Terry produces large stdout/stderr

No streaming output support — entire command output buffered before returning

What makes it unique

Wraps Terry CLI execution in a child process with structured output capture and error handling, mapping MCP tool parameters directly to CLI arguments without shell interpretation

vs alternatives

Safer than shell execution (no injection vulnerabilities) and more reliable than direct library calls, while maintaining full compatibility with Terry's CLI interface

mcp server lifecycle management

Medium confidence

Solves for

Keep MCP server running and responsive to Claude requestsHandle server shutdown cleanly without orphaning child processesManage connection state between MCP client and Terry CLI wrapper

Best for

Production deployments of MCP servers in Claude Desktop or other clients

Teams needing reliable long-running MCP server processes

Automation platforms that spawn and manage MCP server instances

Requires

Node.js event loop and signal handling (built-in)

Proper process management by parent application (systemd, supervisor, etc.)

Standard input/output streams available

Limitations

No built-in health checks or automatic restart on failure

Limited observability — no structured logging or metrics by default

Single-threaded event loop may block on slow Terry commands

What makes it unique

vs alternatives

More robust than naive process spawning by handling OS signals and cleanup, while remaining lightweight compared to full application servers

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

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terry-mcp

Capabilities5 decomposed

terry cli command exposure via mcp protocol

mcp tool schema generation from cli interface

bidirectional stdio communication with mcp clients

terry cli command execution with output capture

mcp server lifecycle management

Related Artifactssharing capabilities

mcp-hello-world

codebase-memory-mcp

Windows CLI

Tmux

phoenix-ai

mcp-cli

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

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Data Sources

terry-mcp

Capabilities5 decomposed

terry cli command exposure via mcp protocol

mcp tool schema generation from cli interface

bidirectional stdio communication with mcp clients

terry cli command execution with output capture

mcp server lifecycle management

Related Artifactssharing capabilities

mcp-hello-world

codebase-memory-mcp

Windows CLI

Tmux

phoenix-ai

mcp-cli

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to terry-mcp

Are you the builder of terry-mcp?

Get the weekly brief

Data Sources