mcp-flowise-connector

mcp-flowise-connector is a Python-based implementation of an MCP server endpoint that establishes connectivity with the underlying Flowise application programming interface. It furnishes a standardized, adaptable mechanism for inventorying conversational flows, generating inference results, and programmatically registering callable functions (tools) specifically for Flowise agents or automated assistants.

It accommodates two distinct execution paradigms:

• Granular Mode (Default): This setting dynamically provisions a distinct service tool for every single chatflow retrieved via the Flowise service endpoint.
• Simplified Mode: This mode provides a curated, static set of tools (list_chatflows and create_prediction), ideal for environments requiring minimal setup overhead.

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Core Capabilities

• Automated Tool Provisioning: In Granular Mode, new tools are instantiated corresponding to every active chatflow or assistant.
• Minimalist Configuration: Simplified Mode offers only list_chatflows and create_prediction utilities for rapid deployment.
• Adaptive Scoping: Both operational methodologies permit the application of precise filtering mechanisms—via inclusion (whitelists) or exclusion (blacklists) lists—based on flow identifiers or names (using regular expressions).
• MCP Compliance: Ensures full compatibility and seamless integration within existing Model Context Protocol infrastructures.

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Deployment Instructions

Installation via Smithery Registry

To deploy mcp-flowise-connector automatically for environments like Claude Desktop using the Smithery registry:

bash npx -y @smithery/cli install @matthewhand/mcp-flowise --client claude

Prerequisites

• An operational Python interpreter, version 3.12 or newer.
• The uvx package management utility.

Installation and Execution via uvx

Verify direct server execution from the source repository using uvx:

bash uvx --from git+https://github.com/matthewhand/mcp-flowise mcp-flowise

Integration into the MCP System (mcpServers Definition)

You can integrate this service into your overarching MCP deployment structure by updating the mcpServers configuration block. Illustration:

{ "mcpServers": { "mcp-flowise-connector": { "command": "uvx", "args": [ "--from", "git+https://github.com/matthewhand/mcp-flowise", "mcp-flowise" ], "env": { "FLOWISE_API_KEY": "${FLOWISE_API_KEY}", "FLOWISE_API_ENDPOINT": "${FLOWISE_API_ENDPOINT}" } } } }

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Operational Regimes

1. Simplified Mode (Activated by FLOWISE_SIMPLE_MODE=true)

This mode: - Exposes only two high-level utilities: list_chatflows and create_prediction. - Permits static definition leveraging FLOWISE_CHATFLOW_ID or FLOWISE_ASSISTANT_ID. - Provides the capability to list all accessible chatflows via list_chatflows.

2. Granular Mode (FLOWISE_SIMPLE_MODE=False)

Key Characteristics: - Automatically generates distinct service methods for every registered chatflow. - Method names are derived from the corresponding chatflow identifier (after normalization). - Utilizes descriptive metadata supplied via the FLOWISE_CHATFLOW_DESCRIPTIONS configuration, defaulting to the flow's name if no description is supplied.

Usage Example: - A callable function process_inquiry(query: str) -> str is dynamically synthesized for a specific flow configuration.

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Execution on Windows Environments using uvx

Users running uvx on Windows may encounter initialization problems when referencing Git repositories directly via --from git+https. The advised remediation involves performing a local repository clone and subsequently configuring mcpServers to utilize the absolute path to uvx.exe alongside the path to the locally cloned directory. Ensure necessary environment variables like APPDATA and LOGLEVEL are explicitly defined.

Exemplary Configuration for Windows MCP Setup (mcpServers Context)

{ "mcpServers": { "flowise": { "command": "C:\Users\matth\.local\bin\uvx.exe", "args": [ "--from", "C:\Users\matth\downloads\mcp-flowise", "mcp-flowise" ], "env": { "LOGLEVEL": "ERROR", "APPDATA": "C:\Users\matth\AppData\Roaming", "FLOWISE_API_KEY": "your-api-key-goes-here", "FLOWISE_API_ENDPOINT": "http://localhost:3000/" } } } }

Important Considerations

• Absolute Paths: Always specify complete file system paths for both the uvx.exe executable and the repository location.
• Environment Pointers: For Windows installations, explicitly define system paths such as APPDATA (e.g., C:\Users\<username>\AppData\Roaming) if required for correct operation.
• Verbosity Control: Configure LOGLEVEL to control output detail (ERROR, INFO, DEBUG, etc.).

Configuration Environment Variables

Universal Settings

• FLOWISE_API_KEY: The mandatory bearer token credential for the Flowise service (essential).
• FLOWISE_API_ENDPOINT: The base Uniform Resource Locator for the Flowise instance (default setting: http://localhost:3000).

Granular Mode Specifics (Default)

• FLOWISE_CHATFLOW_DESCRIPTIONS: A delimiter-separated string mapping flow IDs to custom descriptions. Format example:

FLOWISE_CHATFLOW_DESCRIPTIONS="abc123:First Flow Description,xyz789:Second Flow Description"

Simplified Mode Directives (FLOWISE_SIMPLE_MODE=true)

• FLOWISE_CHATFLOW_ID: Identifier for the singular Chatflow to expose (optional).
• FLOWISE_ASSISTANT_ID: Identifier for the singular Assistant to expose (optional).
• FLOWISE_CHATFLOW_DESCRIPTION: An optional descriptive string for the solitary exposed service method.

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Scoping Mechanism (Filtering Flows)

Filtering capabilities are available across both operational paradigms via the following environment variables:

• Inclusion by Identifier:
  FLOWISE_WHITELIST_ID="id_alpha,id_beta,id_gamma"
• Exclusion by Identifier:
  FLOWISE_BLACKLIST_ID="id_delta,id_epsilon"
• Inclusion by Name (Pattern Matching):
  FLOWISE_WHITELIST_NAME_REGEX=".*core_processor.*"
• Exclusion by Name (Pattern Matching):
  FLOWISE_BLACKLIST_NAME_REGEX=".*obsolete.*"

Important Rule: Inclusion lists supersede exclusion lists. If both filtering mechanisms are defined, the constraint resulting in fewer exposed flows takes precedence.

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Security Posture

• Credential Safeguarding: Exercise extreme caution to ensure that FLOWISE_API_KEY remains confidential and is never committed to public repositories or inadvertently logged.
• Configuration Management: Implement security by managing sensitive variables exclusively through runtime environment injection or secure .env file management.

Reference your .gitignore file to exclude sensitive environment definition files:

bash

.gitignore content excerpt

.env

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Common Diagnostic Procedures

• Credential Failure: Verify that FLOWISE_API_KEY is correctly provisioned and accessible.
• Configuration Conflict: The service initialization will fail if both FLOWISE_CHATFLOW_ID and FLOWISE_ASSISTANT_ID are simultaneously specified.
• Connectivity Problems: Confirm that the network path to the address specified in FLOWISE_API_ENDPOINT is open and responsive.

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Licensing Information

This software is distributed under the terms of the MIT License. Detailed stipulations are available in the accompanying LICENSE file.

Development Roadmap

• [x] Simplified Mode Implementation
• [x] Granular Mode Implementation
• [x] Flow Scoping Logic
• [x] Compatibility for Claude Desktop Integration
• [ ] Native Support for Flowise Assistants

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