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Parzley Server

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Enables AI-powered form filling through natural language by exposing the Parzley AI Form Filling Agent API as an MCP server.

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Описание

Enables AI-powered form filling through natural language by exposing the Parzley AI Form Filling Agent API as an MCP server.

README

Exposes the Parzley AI Form Filling Agent API as an MCP server — enabling Claude Desktop, Claude.ai, and any MCP-compatible client to interact with Parzley natively via natural language.

Requires Python 3.13+ (see pyproject.toml).


Quick start

1. Install the package

From the repository root (use a virtual environment):

pip install .

Or with uv:

uv sync

Dependencies: fastmcp, httpx (declared in pyproject.toml).

If you change pyproject.toml dependencies, run uv lock and commit the updated uv.lock. Hosts that run uv sync --locked (e.g. Railway Railpack) will fail until the lockfile matches.


Connecting to Claude Desktop (local / stdio)

The server entry point is main.py (not the legacy commented parzley_mcp_server.py).

Add the following to your Claude Desktop config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "parzley": {
      "command": "python",
      "args": ["C:/path/to/Parzley_MCP/main.py"]
    }
  }
}

Note: Use the full path to your clone of this repo. command must be a Python 3.13+ interpreter (where python / which python3). On Windows, forward slashes in args are fine.

Restart Claude Desktop completely (quit fully, then reopen). The Parzley tools will appear as a 🔧 hammer icon in the chat input bar.


Connecting to Claude.ai (remote)

Streamable HTTP (recommended; works through Cloudflare) — endpoint /mcp:

python main.py --transport http --port 8001

Then in Claude.ai → Settings → Integrations → Add MCP Server:

  • URL: https://your-domain.com:8001/mcp

SSE (legacy; some setups need Cloudflare proxy adjustments) — endpoint /sse:

python main.py --transport sse --port 8001
  • URL: https://your-domain.com:8001/sse

Railway (or any PaaS)

Deploy is not configured in-repo — set this in your host’s UI (example for Railway):

  1. Builder: Nixpacks (or Railpack), not Dockerfile unless you add your own Dockerfile.
  2. Install: Let Nixpacks auto-detect pyproject.toml, or use a custom install step such as python -m pip install . from the repo root.
  3. Start command: python main.py --transport http --host 0.0.0.0
  4. Port: The platform sets PORT (e.g. 8080). main.py reads PORT from the environment so you do not need --port in the start command.

MCP URL: https://<your-app>/mcp (HTTPS on the host; no port in the URL for a default HTTPS setup).

If deploy still says “Build image” or Docker, switch the service off Dockerfile builder in settings — this repo does not ship a Dockerfile.


Available tools (9 total)

Tool Description
get_form_with_shortcode Resolve a shortcode and start a new form-filling session. Must be called first.
parzley_message_turn Single MCP call that runs concierge_chat and chat_with_agents in parallel — use on every user message after get_form_with_shortcode.
register_respondent Link name + email to the session. Optional in chat — strongly recommended so the user can open and manage their answers in the Parzley web app (browser access is tied to that email). Call after the first successful parzley_message_turn when the user agrees.
get_schema Fetch the full form definition (schema, uiSchema, formContext, etc.) for a MongoDB form_object_id (not a shortcode).
get_form_data_by_session Fetch field values already saved for a session_id.
get_form_data_feedback Feedback on form data quality, gaps, and validation for the session (errors and shortfalls vs concierge “what to ask next”).
submit_form_data Final submission (locks the form); use the 6-character session shortcode.
extract_content Upload a file (PDF or image) to extract raw text / vision description via LlamaParse or VisionAgent (Groq).
analyse_content Upload a file and analyse its content against a user query to map data to form fields.

Session flow

User provides shortcode
        │
        ▼
  get_form_with_shortcode(shortcode)
  ── returns session_id + crew_shortcode
        │
        ▼
  On EVERY user message:
        parzley_message_turn(session_id, …)  ← MCP tool; runs concierge_chat + chat_with_agents in parallel
        │
        ▼
  get_form_data_feedback(session_id)
  ── returns structured document output

Shortcode types

Length Role Behaviour
5 chars Crew / empty template Identifies the empty form for that crew; get_form_with_shortcode starts work against that template. Sending data via parzley_message_turn creates a 6-character session.
6 chars Session + saved data Identifies a specific form instance and answers. Resolved via the API to crew_shortcode and session_id for resume.

File upload tools

Both extract_content and analyse_content accept files as base64-encoded strings and send them to Parzley as multipart/form-data with the raw binary.

extract_content — required fields:

Field Type Description
file_base64 string Base64-encoded file contents
file_name string Original filename with extension (e.g. resume.pdf)
session_id string Session ID from get_form_with_shortcode
form_id string Form ID to extract content for

analyse_content — required + optional fields:

Field Type Required Description
file_base64 string Base64-encoded file contents
file_name string Original filename with extension
session_id string Session ID from get_form_with_shortcode
user_query string Query describing what to extract / analyse
form_id string Form ID to analyse content against
extraction_field string Specific field to target for extraction

Typical Claude conversation

Once connected, try:

"I'd like to fill a form"

Claude will:

  1. Ask for your shortcode
  2. Call get_form_with_shortcode with the shortcode you provide
  3. Store session_id and crew_shortcode for the session
  4. Call parzley_message_turn on every message (it runs the concierge + agent APIs in parallel)
  5. Guide you through the form question by question
  6. Call get_form_data_feedback when you need structured feedback on data quality / gaps

Smoke test (optional)

After install:

python -m unittest tests.test_smoke -v

Notes

  • Timeouts: File upload tools (extract_content, analyse_content) use a 120-second timeout. All other tools use 60 seconds.
  • Parallel calls: The parzley_message_turn tool invokes both HTTP endpoints together; do not call them separately from MCP.

Troubleshooting

Problem Fix
Tools don't appear in Claude Check the config file path, quit and fully reopen Claude Desktop
ModuleNotFoundError Run pip install . from the project root (Python 3.13+)
Server crashes on start Run python main.py in a terminal to see the error
502 on Railway / reverse proxy Confirm main.py is running, PORT matches the platform, and the start command is correct (see Railway above).
File upload fails Ensure the file is properly base64-encoded and file_name has the correct extension
Client says get_form_with_shortcode is missing but lists other Parzley tools The server registers all 9 tools (see parzley_mcp/tools/). The client may be filtering or searching a subset — open the full MCP tool list, reconnect the server, or turn off tool search for the first step. get_form_with_shortcode must run first with the user’s shortcode.

from github.com/l3admin/Parzley_MCP

Установка Parzley Server

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/l3admin/Parzley_MCP

FAQ

Parzley Server MCP бесплатный?

Да, Parzley Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Parzley Server?

Нет, Parzley Server работает без API-ключей и переменных окружения.

Parzley Server — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Parzley Server в Claude Desktop, Claude Code или Cursor?

Открой Parzley Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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