NIRA Video Production MCP

io.github.pachotePublished by GitHub account pachotev1.0.3Updated Oct 24, 2026

Video production MCP: 55 tools — edit, grade, TTS captions, beat-sync, master, AI generate.

VerifiedSTDIODesktop onlyMedia & Design AI & ML

Server details

Identifier: io.github.pachote/nira-video-mcp
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

Security note

MCP servers receive tool arguments from a conversation and may perform external actions. Review what a server can do before you enable it, and give it only the access it needs.

The registry verified the GitHub account pachote for this listing. That does not show the account is the product's maker.

SourceWeft's checks cover whether the listing is complete and the endpoint answered; they do not review the server's code or what its tools do.

Add a badge to your README

Show readers this MCP server is listed on SourceWeft. The badge links to this page.

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.pachote%2Fnira-video-mcp.svg)](https://sourceweft.com/mcp/io.github.pachote%2Fnira-video-mcp?utm_source=readme&utm_medium=badge)

Overview

AI-generated overview

Local MCP server for video production: 55 tools to edit, grade, caption, beat-sync, master and AI-generate video clips.

What you can do: Edit and assemble source clips into finished video productions
Color grade and master rendered output
Add TTS captions and beat-synced cuts
Generate video with cloud AI models (Kling, Luma, Veo, Pika) or a local GPU setup
Read source clips from and write rendered files to configured directories
When to use it: Useful when an assistant should help produce video end to end — cutting and assembling clips, grading, captioning, beat-syncing and mastering — or generate new footage, either through cloud AI video services or a local GPU install.
Requirements: Runs as a local Python package (nira-video-mcp) over stdio on a desktop machine. Needs a fal.ai API key in FAL_KEY for cloud AI video generation, and optionally WAN2GP_PATH pointing to a Wan2GP installation for local GPU generation. Directories for input, output and workspace are set via VIDPROD_INPUT, VIDPROD_OUTPUT and VIDPROD_WORKSPACE.

Before you install

FAL_KEY is a paid third-party API credential; cloud AI video generation sends prompts and source material to fal.ai and may incur charges. The server reads and writes video files in the configured input, output and workspace directories, so point them at folders you are comfortable exposing. Local generation depends on a working Wan2GP GPU setup.

Installation

In SourceWeft

Open NIRA Video Production MCP in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

This repository has no README.

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v1.0.3LatestSep 16, 2026

Score

25% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
Declare a GitHub repository with a README, or serve resource_documentation in the OAuth protected-resource metadata.
License10 pts
Declare a license in the repository or the registry entry.