Overview
ScriptFlow MCP Server is a ScriptFlow component built on the Model Context Protocol (MCP) that transforms complex, repetitive AI interactions into persistent, executable scripts. It enables teams to capture successful AI prompts and workflows as reusable scripts that can be managed, versioned, and reused across sessions. The server provides tools to add, edit, remove, list, search, and execute scripts, each accompanied by metadata such as name, description, content, language, and tags. Scripts are stored on disk with a {name}.{ext} convention and a separate {name}.json metadata file, supporting Bash (.sh), Python (.py), JavaScript (.js), and TypeScript (.ts). It supports multiple languages and aims for deterministic execution by parameterizing inputs. MCP-based tools are exposed for use (script_add, script_edit, script_get, script_list, script_run, script_rm) and can be invoked by MCP clients configured with the provided setup. The default script directory and timeout are configurable via environment variables SCRIPTFLOW_SCRIPTS_DIR (default: /tmp/scriptflow-mcp/scripts) and SCRIPTFLOW_TIMEOUT (default: 30000 ms), respectively, and scripts can be executed with arguments to automate tasks across sessions.
Features
Add/Edit/Remove scripts with metadata
Manage scripts by creating, updating, or deleting scripts along with metadata such as name, description, content, language, and tags.
List/Search scripts by name, description, or tags
Find and filter scripts using name, description, or tags to quickly locate reusable workflows.
Execute scripts with arguments
Run scripts with a provided set of arguments, enabling automated task execution.
Multi-language support (Bash, Python, Node.js, TypeScript)
Create and run scripts in multiple languages to fit various environments and needs.
On-disk storage with language-based file formats and metadata
Persist scripts on disk using {name}.{ext} and {name}.json metadata, with language mappings ( Bash .sh, Python .py, JavaScript .js, TypeScript .ts ).
Who Is This For?
- Teams:Collaborate with colleagues to share proven workflows across the organization, improving consistency.
