
FireCMS Cloud
co.firecmsv3.5.0Updated Sep 30, 2026
Manage FireCMS Cloud from an AI agent: Firestore data, collections, schemas and users.
Overview
Lets an assistant connect a Firebase project to FireCMS Cloud and manage its Firestore data, collection schemas, configuration, and users.
- What it does
- FireCMS Cloud's MCP server exposes tools for Firestore document CRUD (list, get, create, update, delete, count), collection schema management (save, update, delete schemas and properties), project configuration, and user and role administration. It can infer collection schemas from existing Firestore documents, including a non-destructive preview, and AI-generate or modify schemas from a prompt. Onboarding tools list Google Cloud projects, enable APIs, create a Firestore database, and connect a project to FireCMS. It also exports collection data as JSON and bulk-imports documents.
- When to use it
- Use it when you want an assistant to bring an existing Firebase project into FireCMS, infer collections from data already in Firestore, or browse and edit Firestore documents and CMS schemas through chat. It suits ongoing CMS administration such as renaming projects, adjusting brand colors, toggling features, and managing project users.
- Requirements
- Either the hosted remote endpoint (OAuth sign-in in the browser, nothing to install) or the local npm package @firecms/mcp-server over stdio, which needs Node.js and a Google account sign-in via firecms_login. Local tokens are stored in ~/.firecms/tokens.json, shared with the FireCMS CLI. Firebase Authentication must be enabled manually in the Firebase console before connecting a project.
Installation
In SourceWeft
- Open FireCMS Cloud in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.
Other MCP clients
Add this to your client's mcpServers config.
{
"mcpServers": {
"mcp": {
"type": "http",
"url": "https://api.firecms.co/mcp"
}
}
}README
@firecms/mcp-server
MCP server for FireCMS Cloud. Lets AI assistants connect a Firebase project to FireCMS, infer collections from the data already in Firestore, and then manage the CMS — browse and edit data, shape collection schemas and properties, configure the project, and manage users.
Admin-only: All write operations require the authenticated user to have the
adminrole on the target project. Read operations are available to any authenticated project member. Onboarding tools run before a project exists, so they are gated by Google Cloud access instead.
The same server runs in two places:
- Hosted, at
https://api.firecms.co/mcp, for everyone. Clients sign in with OAuth in the browser; nothing to install. It holds no Google Cloud credentials, so connecting a new Firebase project is handed off to the web app. The FireCMS backend mounts it through the@firecms/mcp-server/hostedentry point. - Local, over stdio (
npx @firecms/mcp-server). It signs in with your Google account (firecms_login), so it can also enable APIs, create Firestore databases and connect projects end to end.
Hosted server
In Claude (claude.ai or Claude Desktop): Settings → Connectors → Add custom connector, and paste https://api.firecms.co/mcp.
In Claude Code:
Any other client that takes remote servers by URL:
Local server
Setup
Claude Desktop
Add to claude_desktop_config.json:
Or use npx (no build required):
Use firecms_login to sign in when prompted. Tokens are shared with the FireCMS CLI (~/.firecms/tokens.json).
Connecting an existing Firebase project
The typical first session. Everything here is driven by the Google account you logged in with.
Firebase Authentication must be enabled on the project before step 5 — it is the one prerequisite with no API, so turn it on in the Firebase console. Step 5 then adds FireCMS's access rule to the project's Firestore and Storage rules; without it the CMS reports "Missing Firestore Security Rules" and opens nothing, and no tool here would notice, because they all read through the backend's service account, which bypasses security rules.
Step 6 is where an existing project becomes a working CMS: FireCMS samples the documents at each root collection, infers the property types, and uses an LLM to pick display names, a singular name, an icon and a navigation group.
Building collections from existing data
preview_inferred_schema is the non-destructive option: it samples up to 200 documents, infers types, enums and validation locally, and hands back a draft you can edit and then persist with save_collection_schema. It also works for subcollections and any path the bulk tools skip.
infer_collections_from_data and setup_all_collections go through the backend, which adds the LLM pass and writes the result straight into the project. Both skip paths that already map to a collection, so they are safe to re-run as the database grows.
Tools
Auth
Onboarding
Projects & Root Collections
Project Configuration 🔒
Users 🔒
Collection Schemas 🔒
AI Schema Generation
Documents (Firestore CRUD)
Data Import & Export
🔒 = Admin-only operation · 💻 = local server only
Every tool declares a title and a readOnlyHint, plus a destructiveHint when it writes: false for tools that only add (create a document, invite a user), true for anything that can overwrite or delete.
Resources
Example Workflows
Bring an existing Firebase project into FireCMS
Create a collection from scratch
Shape a schema before committing to it
AI-assisted schema creation
Architecture
Sessions: local and hosted
Nothing reads credentials from process-wide state. Every API call goes through a FireCMSSession (session.ts) — the user's email, a Firebase ID token on firecms-backend, and a Google access token when there is one — passed to createFireCMSMcpServer():
- Local (
cli.ts):localSessionreads the CLI's tokens file and exchanges the Google ID token for a backend token (below). The login/logout tools are registered by the CLI only. - Hosted (
hosted.ts): the backend resolves each request's OAuth bearer token to a user and passes a session that mints that user's backend ID token. There is no Google token, so the Google Cloud tools are replaced by aconnect_project_to_firecmsthat links to the web app. Every request gets its own server and transport (stateless Streamable HTTP), so nothing of one person's session outlives their request.hosted.tsnever imports the CLI's login flow; a test walks its import graph to keep it that way.
Authentication
The FireCMS Cloud API expects two different tokens, and the server sends both — the same pair the web app sends:
firecms login only produces the Google credentials. The Google ID token is not a Firebase ID token — it is issued by accounts.google.com for the Google OAuth client, so verifyIdToken() rejects it. backend-auth.ts therefore exchanges it for a real firecms-backend token through Identity Toolkit signInWithIdp, which is the headless equivalent of the web app's signInWithPopup(auth, GoogleAuthProvider). The exchanged token is cached in memory until shortly before it expires.
Where collection configurations live
FireCMS Cloud reads collection configurations from the backend Firestore, at projects/{projectId}/collections/{collectionId} — see useFirestoreCollectionsConfigController in FireCMSCloudApp.tsx. That is not the client project's __FIRECMS/config/collections, which is the self-hosted layout and is never read by Cloud.
The backend exposes no REST endpoints for that store — the web app writes to it directly with the Firebase SDK — so backend-firestore.ts talks to the Firestore REST API with the exchanged Firebase token. The backend's security rules apply unchanged.
Document CRUD is different: it is proxied by the backend into the client's Firestore using the project's delegated service account.
Cache-aware collection discovery
The backend's firestore_root_collections endpoint caches its answer for 5 minutes per project, so it misses collections created since the last lookup — including every collection of a project connected moments ago. Discovery therefore goes through the uncached admin/collections/list endpoint, and setup_all_collections resolves the paths itself rather than delegating to initial_setup, which resolves them through that same cache.
infer_collections_from_data also refuses paths with no documents. The backend runs its LLM pass regardless, and with nothing to sample the model invents a schema from the path name alone — an empty articles path yields plausible title/slug/status/author fields that exist nowhere in the data.
stdout is reserved
On a stdio transport, stdout carries the JSON-RPC stream, so cli.ts routes every console channel to stderr before starting. Dependencies do log — @firecms/schema_inference logs while inferring properties — and a single stray console.log would corrupt the protocol stream.
Security
- Hosted authentication: OAuth 2.1 with PKCE against the FireCMS backend; the person approves each client in the web app. The backend stores tokens only as hashes, rotates refresh tokens, and never holds Google Cloud credentials
- Local authentication: Google OAuth via browser, same as
firecms loginCLI - Authorization: Write operations enforce admin role check per project
- Token storage:
~/.firecms/tokens.json(shared with CLI); the exchanged backend token is held in memory only and dropped on logout - Admin cache: Role checks are cached for 5 minutes per project
- Credential hygiene:
list_projectsstrips each project's service account from its output, so credentials are never serialised into the model's context
Source: packages/mcp_server/README.md at commit 74bd4a2
Tools
0Version history
1- v3.5.0LatestSep 30, 2026

