PsyFlow-MCP

PsyFlow‑MCP · Usage Guide

A lightweight FastMCP server that lets a language‑model clone, transform, download and local‑translate PsyFlow task templates using a single entry‑point tool.

1 · Install & Run

# 1. Clone your project repository
git clone https://github.com/TaskBeacon/psyflow-mcp.git
cd psyflow_mcp

# 2. Install runtime deps
pip install "mcp-sdk[fastmcp]" gitpython httpx ruamel.yaml

# 3. Launch the std‑IO server
python main.py

The process stays in the foreground and communicates with the LLM over STDIN/STDOUT via the Model‑Context‑Protocol (MCP).

2 · Conceptual Workflow

User describes the task they want (e.g. “Make a Stroop out of Flanker”).
LLM calls the tool:\ • If the model already knows the best starting template it passes `source_task`.\ • Otherwise it omits `source_task`, receives a menu created by, picks a repo, then calls `` again with that repo.
The server clones the chosen template, returns a Stage 0→5 instruction prompt (``) plus the local template path.
The LLM edits files locally, optionally invokes `` to localise config.yaml, then zips / commits the new task.

3 · Exposed Tools

Tool	Arguments	Purpose / Return
`build_task`	`target_task:str`, `source_task?:str`	Main entry‑point. • With `source_task` → clones repo and returns: `prompt` (Stage 0→5) + `template_path` (local clone). • Without `source_task` → returns `prompt_messages` from `` so the LLM can pick the best starting template, then call `build_task` again.
`list_tasks`	none	Returns an array of objects: `{ repo, readme_snippet, branches }`, where `branches` lists up to 20 branch names for that repo.
`download_task`	`repo:str`	Clones any template repo from the registry and returns its local path.
`translate_config`	`task_path:str`, `target_language:str`	Reads `config.yaml`, wraps it in ``, and returns `prompt_messages` so the LLM can translate YAML fields in‑place.

Why a single entry‑point? build_task already covers both “discover a template” and “explicitly transform template X into Y”. Separate transform_task became redundant, so it has been removed.

4 · Exposed Prompts

Prompt	Parameters	Description
`transform_prompt`	`source_task`, `target_task`	Single User message containing the full Stage 0→5 instructions to convert `source_task` into `target_task`.
`choose_template_prompt`	`desc`, `candidates:list[{repo,readme_snippet}]`	Three User messages: task description, template list, and selection criteria. The LLM must reply with one repo name or the literal word `NONE`.
`translate_config_prompt`	`yaml_text`, `target_language`	Two‑message sequence: strict translation instruction + raw YAML. The LLM must return the fully‑translated YAML body with formatting preserved and no commentary.

5 · Typical Call‑and‑Response

5.1 – Template Discovery

{ "tool": "build_task", 
    "arguments": { "target_task": "Stroop" } 
}

Server → returns prompt_messages .

5.2 – LLM Chooses Template & Requests Build

{ "tool": "build_task", 
    "arguments": { "target_task": "Stroop", 
                   "source_task": "Flanker" } 
}

Server → returns Stage 0→5 prompt + template_path (cloned Flanker repo).

5.3 – Translating YAML (Optional)

{ "tool": "translate_config", 
        "arguments": { "task_path": "/abs/path/Flanker", 
                       "target_language": "zh" } 
}

Server → returns prompt_messages; LLM translates YAML and writes it back.

6 · Template Folder Layout

<repo>/
├─ config/
│  └─ config.yaml
├─ main.py
├─ src/
│  └─ run_trial.py
└─ README.md

Stage 0→5 assumes this structure.

Adjust NON_TASK_REPOS, network timeouts, or git clone depth to match your infrastructure.

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A lightweight FastMCP server that enables language models to discover, clone, transform, and localize PsyFlow task templates through a streamlined workflow with standardized tools.

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PsyFlow-MCP

PsyFlow‑MCP · Usage Guide

1 · Install & Run

2 · Conceptual Workflow

3 · Exposed Tools

4 · Exposed Prompts

5 · Typical Call‑and‑Response

5.1 – Template Discovery

5.2 – LLM Chooses Template & Requests Build

5.3 – Translating YAML (Optional)

6 · Template Folder Layout

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