Floyo MCP

use floyo mcp to connect ai agents to floyo over the model context protocol https //modelcontextprotocol io once connected, your agent can discover workflows, start runs, inspect outputs, and upload files into your team’s private storage — all from chat, without opening the floyo app introduction floyo mcp is a remote mcp server hosted by floyo your agent talks to the server over https; the server translates tool calls into authenticated requests to floyo on your behalf workflows execute on floyo infrastructure, so you do not need a local gpu mcp server url https //mcp floyo ai/mcp any mcp compatible client that supports remote http transport and oauth can connect this page covers first class setup for claude desktop / web, claude code, chatgpt, codex, cursor, antigravity ide, and antigravity cli prefer raw http and api keys for scripts or ci? see floyo api introduction https //docs floyo ai/floyo api introduction instead floyo mcp is designed for interactive agents and uses floyo oauth — you never paste a floyo api key into your agent config install instructions you need a floyo https //www floyo ai account before connecting during setup, your client opens a browser so you can sign in with floyo oauth and approve access open the client you use claude desktop / web claude connects floyo as a custom connector , then completes floyo oauth in the browser you can add the floyo mcp to claude with a one click link or set it up manually through the settings panel one click installation manual installation open settings panel open customize → connectors (on claude ai https //claude ai or in claude desktop) add a custom connector named floyo and set the remote mcp server url to https //mcp floyo ai/mcp click add to save the connector authenticate with floyo after adding the mcp using either method, you’ll be prompted to connect click connect , then complete the oauth authentication flow in the browser window that opens after connecting, ask in plain language — for example, “list my floyo teams” or “find a text to image workflow on my team ” claude code add floyo as a remote http mcp server, then authenticate register the server claude mcp add transport http floyo https //mcp floyo ai/mcp run /mcp , select floyo , and choose authenticate complete floyo oauth in the browser tokens refresh automatically afterward chatgpt open chatgpt → settings → plugins → mcps and click on + add server on the connect to a custom mcp screen set floyo as the mcp name , select streamable http , use https //mcp floyo ai/mcp as url and click save back to the mcps list, click on authenticate next to floyo mcp this will start the oauth flow after connecting, ask in plain language — for example, “list my floyo teams” or “find a text to image workflow on my team ” codex codex https //developers openai com/codex/cli connects over streamable http add the server, then sign in with floyo oauth register and log in codex mcp add floyo url https //mcp floyo ai/mcp codex will detect that the floyo mcp needs authentication and will open a browser window to guide you through the oauth flow if it doesn’t start the authentication process automatically, simply run codex mcp login floyo approve access in the browser when prompted this writes an entry to / codex/config toml (or codex/config toml in a trusted project), for example \[mcp servers floyo] url = "https //mcp floyo ai/mcp" ask in plain language after login — codex invokes floyo tools on your behalf cursor one click installation cursor will open with the mcp configuration already prefilled click install to add the mcp once the installation is complete, it will appear under installed mcp servers finally, click authenticate and complete the oauth authentication flow manual installation cursor connects to floyo mcp over http and completes floyo oauth you do not put a floyo api key in mcp json open cursor settings → tools & mcp add a custom mcp server, or edit / cursor/mcp json (global) / cursor/mcp json (project) { "mcpservers" { "floyo" { "url" "https //mcp floyo ai/mcp" } } } when cursor prompts for authentication, sign in with floyo and approve access confirm floyo tools appear under mcp, then ask in plain language (for example, “discover verified workflows on my team”) antigravity open settings → customizations and click on open mcp config your os file browser will open to antigravity's mcp config json file open the file in your favourite text editor edit mcp config json to include floyo under mcpservers like this { "mcpservers" { "floyo" { "serverurl" "https //mcp floyo ai/mcp" } } } save the file go back to antigravity and click on refresh button floyo mcp will appear on the installed mcp servers list click on the authenticate button you'll be taken through the oauth flow after authorizing the agent you'll get an authorization code go back to antigravity and paste the code then click submit antigravity cli antigravity cli uses the same remote schema as the ide prefer the interactive mcp manager after the config entry exists add floyo to / gemini/antigravity cli/mcp config json (global) or agents/mcp config json (workspace) { "mcpservers" { "floyo" { "serverurl" "https //mcp floyo ai/mcp" } } } in the cli prompt panel, run /mcp to open the mcp manager and confirm floyo is listed select floyo mcp, use the arrow keys to select authenticate a browser window will open to authorize antigravity to connect to your floyo account after authorizing the agent you'll get an authorization code copy the code paste the code back to antigravity cli to finish setup reload the server from /mcp if the connection shows as disconnected after login authentication floyo mcp authenticates with floyo oauth your mcp client opens a browser consent flow; after you approve, the client stores tokens and refreshes them as needed we care about your api keys security floyo mcp does not need an api key at all floyo api keys are reserved for api only usage mcp authentication is oauth only , so your api keys are never pasted into agent configs and never shared with an ai agent or third party mcp host sign in once in the browser; the agent works under your floyo identity without ever holding a long lived key what oauth unlocks the agent acts as you , the signed in floyo user your memberships, roles, and team private assets follow that identity — see work under a team context /#work under a team context work under a team context floyo mcp is built around floyo teams after you sign in, you can work under any team you belong to — personal or shared — with the same oauth session runs, files, uploads, and team workflow discovery stay inside the team you select you do not need to memorize team ids talk to your agent in plain language what you want example prompt see every team you can use list my teams start (or lock) a team for the conversation work under \[team name] context change teams later switch to \[team name] team the agent keeps the active team ai agents are smart enough to remember the team context for the conversation you do not need to restate which team to use before every prompt once you say something like work under acme studio context , later requests — discover workflows, run a job, list recent runs, upload a file — should execute under that team until you switch if you are unsure which team is active, ask which team are we working under? switch anytime team context is not permanent change it whenever you need a different workspace switch to \[team name] team use my \[team name] team for the next runs after a switch, subsequent tool calls should use the new team assets and run history from the previous team stay isolated there why team context matters on floyo floyo mcp treats teams as a first class security and collaboration boundary — not an afterthought you stay you oauth maps to your floyo user the agent only sees teams you already belong to; it cannot invent access to someone else’s workspace hard isolation workflows, runs, uploads, and downloads for a team stay in that team’s private storage switching context changes which vault the tools talk to shared workspaces, individual consent invite collaborators on floyo as usual each person connects mcp with their own oauth login — no shared api keys in agent configs, and no key sprawl across laptops or ci secrets for chat agents roles follow floyo what you can list or run respects the same team membership you have in the floyo app revoke a member in floyo and their agent loses that team context on the next authorized call clear mental model one signed in user, many teams, one active context at a time ask list my teams , pick a name, and keep chatting prefer browsing public community workflows? you can still ask the agent to discover public workflows for anything that creates runs, uploads files, or reads team history, set an active team first available tools and apps you do not call mcp tools yourself your agent chooses tools from what you ask plain language is enough — for example, “list my teams,” “find an upscaler workflow,” or “run this on my active team ” typical flow set team context — list my teams , then work under \[team name] context discover a workflow (team scoped, or public when browsing the community) upload inputs when needed via the upload widget run the workflow, then check status and outputs tools tool description list user teams lists floyo teams available to the signed in user each id is the public team id to pass as team id elsewhere get team balance retrieves the active team’s flotime and partner nodes balance (plan allocation, flex flotime, reserved/active usage, and usd partner nodes) discover workflows searches and filters floyo workflows (search, tags, sort, scope, verification, pagination, optional field expansion) list team runs lists workflow runs for a team, with filters, sorting, pagination, and optional expansions (outputs, costs, and more) run workflow creates a floyo run from comfy api workflow json for the selected team prefer discovering a workflow with expand including prompt , then pass that prompt as workflow retrieve run retrieves a single run by id for the active team, optionally with presigned output urls or partner nodes cost details list files browses team storage (files and folders) for a path, with search, sort, size/date filters, and cursor pagination retrieve file retrieves file metadata for a team owned file, optionally with a temporary presigned download url delete file permanently deletes a file or folder by id use recursive to delete a non empty folder and its contents prepare file upload opens the floyo upload widget and creates a short lived upload session for the selected team deleting files is permanent delete file removes items from your team’s storage with no undo through floyo the tool instructs agents to confirm with you first, but that is not a guarantee — behavior depends on the model and your mcp client if tool calls are auto approved (or you said something like “clean up my uploads”), the agent may delete without asking again prefer clients that require approval for each tool call when cleaning storage, name the exact file or folder you want removed, and treat recursive folder deletes as a full wipe of that tree root folders such as inputs and outputs cannot be deleted upload widget floyo mcp includes an interactive upload mcp app for attaching images and other inputs to your team in a single session you can upload up to 10 files , each no larger than 90 mb limited widget support the widget is currently supported only by chatgpt and claude web/desktop cli applications do not support interactive html widgets when your agent calls prepare file upload floyo creates a short lived upload session for the chosen team id the upload widget opens in your mcp client you pick a file on your device the file is uploaded directly from your device to floyo’s cdn into your team’s private, secure storage we care about your files privacy and security file bytes never travel through the mcp host, the language model, or third party agent infrastructure the widget redeems short lived cdn credentials privately inside the app; those credentials are not shown to you or to the model only session metadata needed to complete the upload is exchanged with the agent tools after a successful upload, your agent can use the resulting file ids with workflows and runs under the same team context