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mcp.film directory

by c47-incversion 1.6.0i★ –iComputer or cloud
Registry namefilm.mcp/directory

Install

Overview

Description from the maker (original English)

Search the curated directory of MCP servers for AI filmmaking and plan a full production stack.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Computer or cloud
  • Transport: stdio, Streamable HTTP
  • Category: Games, sports, food & learning

Install

Pick the AI app you use, then copy the settings.

Before you install

You need

  • Runs in the cloudNothing to install; it connects over the internet
  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

  1. Open Settings → Connectors
  2. Press Add custom connector
  3. Paste the address below and press Add
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Add2https://…3
https://mcp.film/mcp

Or run it on your computer

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "directory": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-film"
      ]
    }
  }
}

Run this in your terminal

claude mcp add --transport http directory https://mcp.film/mcp

Or run it on your computer

claude mcp add directory -- npx -y mcp-film

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "directory": {
      "url": "https://mcp.film/mcp"
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "directory": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-film"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "directory": {
      "type": "http",
      "url": "https://mcp.film/mcp"
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "directory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mcp-film"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

  1. Open ChatGPT on the web → Settings → Connectors (Apps)
  2. Press Create or Add (some plans need Developer mode under Advanced first)
  3. Paste the address below, give it a name and save
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Create2https://…3
https://mcp.film/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Tool names and descriptions exactly as the server reported them on Nov 7, 2026. The maker wrote them, not us; we show them as plain text.

  • search_film_mcps

    Search the mcp.film directory of MCP servers for AI filmmaking. Filter by free-text query (matches name, vendor, tagline, description, capabilities, tools, category, pricing, auth, and the creative apps a server drives by name or alias, e.g. 'c4d' or 'resolve'), category id, or c

  • get_film_mcp

    Get the full mcp.film entry for one server by slug: description, install commands, auth requirements, sample tools, links, field notes (caveats), and machine-checked evidence (evidence level, last_probe of the hosted endpoint, package_check).

  • list_film_categories

    List all mcp.film categories with ids, pipeline stage, and per-category agent hints.

  • list_film_capabilities

    List capability tags in the mcp.film registry, ranked by number of matching servers (tag, page url, counts). Paged. Use get_film_capability for the server cluster behind one tag.

  • get_film_capability

    Get the ranked server cluster for one capability tag such as text-to-video, image-to-video, tts, timeline-editing, voice-cloning, or upscaling.

  • get_install_config

    Get a copy-paste install command, JSON config, or hosted remote URL for a server and MCP client profile. Includes required env vars and auth type.

  • list_client_profiles

    List the MCP client setup profiles mcp.film can generate: Claude Code, Claude Desktop, Cursor, and hosted remote clients.

  • submit_listing

    Propose a new MCP server for the mcp.film directory. Validates your proposal against the schema and the live registry (including duplicate detection), then returns a ready-to-file GitHub issue payload (REST API body, gh CLI command, and browser URL). Submissions are claims, never

  • get_catalog_pulse

    Get the mcp.film operating pulse: catalog freshness, verification queue, curator agenda, and machine-readable surfaces. Use this before deciding what to update next. The curator/ops sections demand_signals and martini_growth_checks are opt-in by section and not part of 'all'.

  • list_film_playbooks

    List mcp.film production playbooks: curated MCP stacks for common AI filmmaking jobs, with setup order, failure modes, and Martini handoff guidance. Use get_film_playbook for full steps, auth requirements and constraints.

  • get_film_playbook

    Get one production playbook by id, including primary servers, setup order, auth requirements, workflow steps, failure modes, fallback servers, constraints, and links to each server's mcp.film page. Pass client (claude_code, claude_desktop or cursor) to get only a copy-paste insta

  • list_film_recommendations

    List mcp.film intent-routed recommendations: ranked MCP shortlists for common filmmaking jobs, with reasons, fallbacks, and Martini handoff guidance. Use get_film_recommendation for full detail.

  • get_film_recommendation

    Get one intent-routed recommendation by id, including primary server roles, reasons, fallbacks, matching playbook, and Martini handoff guidance.

  • recommend_film_mcps

    Given a filmmaking brief, return the closest intent-routed MCP recommendations: one compact pick per primary server (slug, role, why, remote, official, verified) plus compact fallbacks. Use hosted_only=true when the agent cannot spawn local tools; get_film_mcp for full server det

  • plan_film_stack

    Get a recommended set of MCP servers covering the whole film pipeline (develop → visualize → shoot → sound → cut → finish → ship). Returns 1-3 picks per stage, ranked by official status and hosting. Pass a brief to bias picks (matched against capabilities, taglines and descriptio

  • get_martini_setup

    Ordered, executable runbook for connecting a user to Martini (the sponsor's full-stack AI film studio) with the fewest human steps: a resumable state model (needs_account → needs_authorization → needs_billing → needs_project → ready), the human steps, agent steps tailored to the

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified against the domain mcp.film (the registry checks domain ownership)

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • ✓ Pass

    Endpoint responds

    Responded in 66 ms (HTTP 200)

  • – Not applicable

    Sign-in with OAuth

    No sign-in needed

  • ✓ Pass

    No hidden instructions in tool descriptions

    Read 16 tool descriptions and found no hidden instructions to the AI

Compared with others in Games, sports, food & learningi

  • More stars than 0% of the other 1283 servers in this category
  • Published to the registry more recently than 75% of the other 1283 servers in this category
  • Basic checks equal to or better than 100% of the other 1283 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is mcp.film directory safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.6.0) reached the registry 11 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: slopped.site, Artsonia MCP, Canvas Parent MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

slopped.site

by slopped.site

Read-only tools over slopped.site: AI-made art, lore, games, sites, the curriculum.

Runs in the cloudUpdated today
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Artsonia MCP

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Parent/fan access to Artsonia student-art portfolios, comments, and fans (AI-built).

Runs on your computerUpdated today
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Canvas Parent MCP

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Canvas LMS (Instructure) for Claude — courses, grades, assignments, planner, files

Runs on your computerUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

mcp-film

The mcp.film directory as an MCP server. Give your agent a map of every MCP server worth knowing in AI filmmaking — searchable by capability, with copy-paste install configs and a full-pipeline planner.

claude mcp add mcp-film -- npx -y mcp-film

Or connect the hosted endpoint — same tools, no local install:

claude mcp add --transport http mcp-film https://mcp.film/mcp

Speaks MCP 2025-11-25, 2025-06-18 and 2025-03-26 (an unknown offered version gets the latest). initialize returns short instructions: start with recommend_film_mcps(brief).

Tools

ToolWhat it does
recommend_film_mcpsMatch a free-text brief to the best routes and first servers to connect. Hard constraints first (constraints object or phrases in the brief), then relevance; confidence says how well the brief matched
search_film_mcpsTokenised, alias-aware search (lipsync = lip-sync = lip sync; tts = text to speech; 4k = upscale; creative-app names and aliases such as c4d, resolve or fcp find the servers that drive that app); filter by category, capability, official, remote, answering_only (hosted endpoint answered the daily check); paged
get_film_mcpFull entry for one server: install, auth, tools, caveats, status, evidence level and last endpoint/package check
list_film_categoriesAll categories with pipeline stages and agent hints
list_film_capabilitiesCapability tags (aliases folded in) ranked by server count; min_count 2 by default; paged
get_film_capabilityRanked server cluster for one tag; aliases resolve (lipsync → lip-sync, says resolved_from); paged
get_install_configCopy-paste config or hosted remote URL for a client from list_client_profiles; a bad client returns valid_clients
list_client_profilesSupported MCP client setup profiles and install-shape hints
get_martini_setupExecutable runbook for connecting a user to Martini (the sponsor): resumable state model, human steps, agent steps per client / shell / browser, quote-first generation contract, structured cost, when not to
get_catalog_pulseOperating pulse: freshness, verification queue, curator agenda, machine surfaces. demand_signals and martini_growth_checks are curator/ops sections served only by name
list_film_playbooksCurated production stack recipes for common AI filmmaking jobs; paged
get_film_playbookFull playbook with primary servers, setup order, auth requirements, steps, constraints, fallbacks. Pass client (claude_code, claude_desktop, cursor) for only a copy-paste install of the whole stack
list_film_recommendationsIntent-routed MCP shortlists for common filmmaking jobs; paged
get_film_recommendationFull recommendation with roles, reasons, fallbacks, and Martini handoff guidance
plan_film_stackRecommended servers for every pipeline stage, biased by your brief (capabilities, taglines, descriptions)
submit_listingPropose a new server: validated, deduped against the live registry, returned as a ready-to-file GitHub issue payload (a mcp.film maintainer verifies against primary sources before listing)

Response shapes

Every result is compact JSON in content[0].text and the same object in structuredContent.

Lists (search_film_mcps, get_film_capability, list_film_capabilities, list_film_playbooks, list_film_recommendations) carry count, total, limit, offset, next_offset and truncated. Nothing is cut silently: pass offset: next_offset for the next page. Default limit is 20 (50 for capabilities), maximum 100.

Compact server (search results, capability clusters, stack picks): slug, url, verified, caveat, name, vendor, official, category, tagline, pricing, remote, evidence, capabilities plus status when the listing carries one. caveat is the entry's caveats[0], else the first sentence of its notes that is not a verification log line. get_film_mcp is always the full entry.

Recommendation pick (recommend_film_mcps): primary_servers[] and the alias primary[] hold {slug, name, role, why, remote, official, verified, status?, caveats?}; fallback_servers[] hold {slug, name, remote, official, verified, status?}. Pass verbosity: "full" for the complete server objects. Each route has match: {score, strength}; the reply has confidence (strong | fair | weak). When Martini is a primary pick or the brief asks for production state, the route carries martini_handoff (prose) and martini_handoff_structured (when, not_when, first_calls, install {mcp, cli}, signup_url, setup_tool, tracked_url, disclosure).

Constraints (recommend_film_mcps): constraints: {local_only, no_upload, hosted_only, has_shell, free_only, os}, also inferred from phrases such as "locally", "without uploading", "confidential", "offline", "no budget", "free tools", "no local install". Violating picks are removed before scoring and named in excluded_by_constraints; if nothing survives, the reply is no_match with unsatisfied_constraints and relevant_routes.

Whole-stack install (get_film_playbook with client): {id, title, url, install_script, note}. install_script is {client, servers, script} for claude_code (one commented claude mcp add line per server) or {client, servers, file, config, note} for claude_desktop / cursor (one merged mcpServers object), plus checklist[] (slug, name, auth, env_var?, where?: the keys, OAuth sign-ins and local apps the stack needs) and skipped[] (slug, name, reason, listing). Primary and workflow servers only, never fallbacks. Retired listings, listings with install.generate: false, and listings with no mechanical install for that client are skipped with the reason, never guessed at. It is the same block shown on mcp.film/playbooks/{id}/ and in its .md.

Evidence. Every server carries evidence, derived at build time from a daily anonymous check (no LLM, no credentials, tools are never called): endpoint_answered (the hosted endpoint completed an MCP initialize, or answered with a 401/403 sign-in challenge, within the last 7 days) > package_resolves (its npm/PyPI package exists, checked within 7 days) > docs_checked (only the curator's verified date). get_film_mcp adds last_probe: {date, result, protocol_version, tool_count, anonymous_tools_list, auth_required, oauth_metadata, consecutive_failures, last_ok} (result: ok | auth_required | handshake_only | error | unreachable) and package_check: {date, registry, name, found, latest_version, last_ok}, each null when not applicable. A failing check never changes status; a curator does that after re-verifying.

Status. Listings with status dead, archived or deprecated are hidden from search, recommendations and stack plans unless include_inactive: true.

Zero results. search_film_mcps returns did_you_mean (nearest capabilities, categories, servers) and a hint; an unknown category or capability is an error carrying valid_categories / did_you_mean.

How it works

Zero dependencies. Fetches the live registry from https://mcp.film/api/registry.min.json and production playbooks from https://mcp.film/api/playbooks.json, plus recommendation routes from https://mcp.film/api/recommendations.json and the operating pulse from https://mcp.film/api/pulse.json (5s timeout each), then falls back to bundled snapshots offline. Live data is cached for an hour and refreshed in the background (MCP_FILM_CACHE_TTL_MS); MCP_FILM_OFFLINE=1 serves the snapshots only and MCP_FILM_API_BASE points the fetch at another host. get_catalog_pulse reports data_source and observed_at. Data is curated and re-verified continuously at github.com/c47-inc/mcp-film.

MIT.

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