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Tallyfy

Tallyfy MCP server with Google Gemini

Run Tallyfy by chatting in Google Gemini

Connect Tallyfy to Google Gemini and you can run your workflows just by typing in plain English. Ask Gemini to find your overdue tasks, launch a process, or point out where work is getting stuck, and it does the work in Tallyfy for you. No clicking through screens.

There are three ways to connect, and which one you pick depends on who’s using it. The setup for each is further down, under For developers.

What you can do

Once Tallyfy is connected, you just talk to Gemini and it handles the rest. For example, you can ask it to:

  • Find all your overdue tasks and summarize them grouped by who they’re assigned to.
  • Look at last month’s onboarding processes and point out where they slow down.
  • Review one of your templates and suggest ways to improve it.
  • Watch your running work and flag anything at risk of missing its deadline, with a guess at why.

Because Gemini lives inside Google’s tools, you can also mix Tallyfy with the rest of them. Pull process timings next to data in BigQuery, kick off a review in Tallyfy when a new file lands in Cloud Storage and ping the team in Gmail, or have Gemini read an image or document as part of a review. Gemini handles pictures and files, not just text.

Which way should you connect?

  • Gemini CLI - the command-line tool, for developers who work in a terminal.
  • Gemini Code Assist - the same thing, but inside the VS Code or IntelliJ code editor.
  • Gemini Enterprise - for a whole team. Your Google Cloud admin sets it up once, then everyone can use it. This one is in Preview right now.

The first two take about a minute. The Enterprise setup is more involved and your Google admin handles it. All three steps are under For developers.

Good to know

  • Enterprise is in Preview. As of May 2026, the Gemini Enterprise setup screens and field names may still change.
  • Your admin turns tools on. After Enterprise setup, each Tallyfy tool starts switched off. An admin enables the ones your team should use.
  • Chat is text only. Gemini shows you text, so Tallyfy’s visual tracker won’t appear in the chat. You ask for status updates in words instead.
  • Tallyfy isn’t in a public Gemini directory. Each organization adds Tallyfy itself using the steps below. It won’t show up on its own.

Is it secure?

Yes. You sign in with your own normal Tallyfy login through OAuth1, the same secure sign-in standard banks and big apps use, so you never paste a password into Gemini. Your sign-in is tied to your Tallyfy organization, and access tokens refresh on their own in the background. Enterprise teams also get Google’s Vertex AI controls and audit logs in Cloud Logging. Full details are in For developers.

For developers

(Skip this unless you’re setting up the technical side.)

Server endpoints

Tallyfy publishes two endpoints for Gemini, and they behave identically:

  • Primary: https://mcp.tallyfy.com/ (hosted on DigitalOcean).
  • Google Cloud Run mirror: https://mcp-gcp.tallyfy.com/ (the Tier-1 choice for Gemini Enterprise).

Both expose the same 107 tools and share the same OAuth backend, so your access tokens work on either one. The server is listed on the Official MCP Registry ↗ as com.tallyfy/mcp-server.

The Cloud Run mirror is operationally identical to the primary endpoint but runs on Google Cloud Run. For Gemini Enterprise that means lower-latency egress, easier VPC Service Controls and Cloud Logging integration, and an origin that lives inside Google’s compliance perimeter. The deploy pipeline (Cloud Build, then Artifact Registry, then Cloud Run) is fully operational, and every push to the MCP server repo deploys to both endpoints in parallel. Pick whichever endpoint your AI surface prefers - the data and behavior are the same.

Gemini MCP support status

  • Gemini CLI - remote streamable-HTTP MCP via ~/.gemini/settings.json; OAuth auto-discovered through DCR and PKCE.
  • Gemini Code Assist - same configuration schema as Gemini CLI in VS Code; IntelliJ uses mcp.json.
  • Gemini Enterprise - Custom MCP Server data store (Preview); per-organization configuration in the Google Cloud Console.
  • Apigee integration - an optional path for converting managed APIs into MCP servers (not needed for Tallyfy; we publish our own server directly).

Prerequisites

  • A Tallyfy account with an active organization.
  • For the Gemini CLI path: @google/gemini-cli installed (npm install -g @google/gemini-cli).
  • For Gemini Code Assist: the Code Assist extension installed in VS Code or IntelliJ, signed in to a Google account with Gemini access.
  • For Gemini Enterprise: Discovery Engine Editor IAM role (roles/discoveryengine.editor) plus the ability to override the org policy that blocks custom MCP server data stores.

Connect Tallyfy in Gemini CLI

  1. Install the CLI

    Terminal window
    npm install -g @google/gemini-cli
    gemini --version

  2. Add Tallyfy to your settings

    Edit ~/.gemini/settings.json (or .gemini/settings.json inside a project):

    {
      "mcpServers": {
        "tallyfy": {
          "httpUrl": "https://mcp.tallyfy.com/"
        }
      }
    }

    That’s the entire config. The CLI handles OAuth automatically through Dynamic Client Registration plus PKCE the first time Tallyfy responds with a 401. You don’t need to paste a client ID, client secret, or any OAuth endpoint URLs.

  3. Restart Gemini CLI

    Quit any running session, then re-launch:

    Terminal window
    gemini

  4. Verify the connection

    Inside the Gemini chat, run:

    /mcp list

    You’ll see tallyfy listed with 107 tools.

  5. First use authorizes you

    The first prompt that calls a Tallyfy tool opens a browser tab where you sign in to Tallyfy and pick which organization to connect.

Connect Tallyfy in Gemini Code Assist

  1. VS Code

    Add the same mcpServers block to ~/.gemini/settings.json. Reload the Gemini Code Assist extension (Cmd+Shift+P then Developer: Reload Window). Then run /mcp list in the chat panel.

  2. IntelliJ

    Create mcp.json in the IDE’s Gemini config directory with the same content. Restart the IDE and verify with /mcp list.

  3. Same OAuth flow

    Both IDEs use the same Dynamic Client Registration flow. Your browser opens for sign-in the first time you call a Tallyfy tool.

Connect Tallyfy in Gemini Enterprise

Gemini Enterprise’s Custom MCP Server data store (Preview as of May 2026) is configured per-organization by your Google Cloud admin. The connection setup happens entirely on Google’s side. There’s no approval step or vendor signup at Tallyfy.

  1. Override the org policy

    Custom MCP server data stores are blocked by default at the organization level. Your admin overrides the policy following Google’s setup documentation ↗.

  2. Grant Discovery Engine Editor

    Assign roles/discoveryengine.editor to the admin who’ll create the data store, via the IAM page in Cloud Console.

  3. Register an OAuth client for Tallyfy

    Tallyfy supports Dynamic Client Registration. Register a confidential client for Gemini Enterprise with one curl call. The server advertises both client_secret_basic and client_secret_post as supported token endpoint auth methods - Gemini Enterprise typically uses client_secret_basic, but either works:

    Terminal window
    curl -s -X POST https://mcp-gcp.tallyfy.com/mcp/oauth/register \
      -H "Content-Type: application/json" \
      -d '{
        "client_name": "Gemini Enterprise - YourOrgName",
        "redirect_uris": ["https://vertexaisearch.cloud.google.com/oauth-redirect"],
        "grant_types": ["authorization_code","refresh_token"],
        "response_types": ["code"],
        "token_endpoint_auth_method": "client_secret_basic"
      }'

    The response contains both client_id and client_secret. Save both - you’ll paste them into the Cloud Console in the next step. You can register against either endpoint (mcp.tallyfy.com or mcp-gcp.tallyfy.com); the credentials are valid on both because they share the OAuth backend.

  4. Add the data store in Cloud Console

    In Google Cloud Console: Gemini Enterprise -> Data stores -> Create data store -> Custom MCP Server (Preview) -> Add MCP server. Fill the form using the Cloud Run mirror so your origin stays inside Google’s network:

    FieldValue
    MCP Server URLhttps://mcp-gcp.tallyfy.com/
    Authorization URLhttps://mcp-gcp.tallyfy.com/mcp/oauth/authorize
    Token URLhttps://mcp-gcp.tallyfy.com/mcp/oauth/token
    Client ID(from step 3 response)
    Client Secret(from step 3 response)
    Token endpoint auth methodclient_secret_basic (or client_secret_post)
    Scopesmcp.users.read mcp.tasks.read mcp.tasks.write mcp.processes.read mcp.processes.write mcp.templates.read mcp.templates.write mcp.forms.read mcp.forms.write mcp.automation.read mcp.automation.write

    If you prefer the DigitalOcean origin, swap all three URLs to mcp.tallyfy.com - the behavior is identical.

  5. Add a server description

    In the MCP Server Description field, paste this starter (Google uses it for routing decisions):

    Tallyfy manages business workflows, processes, and task assignments. Use this server when the user asks about:
    - Running, launching, or tracking workflow processes
    - Assigning, completing, or commenting on tasks
    - Creating or editing process templates and form fields
    - Managing approval flows and automation rules
    - Viewing process performance or finding bottlenecks
    

    Example queries that route here:
    - "Show me overdue tasks in Tallyfy"
    - "Launch a new vendor onboarding process for ACME Corp"
    - "What's the average completion time for our customer support workflow?"
    - "Add a new step to the invoice review template"

    Adjust this for your team’s vocabulary.

  6. Finalize and reload

    Select a Multi-region location, give the data connector a name, and click Create. Wait for the state to change to Active. Then go to Actions -> Reload custom actions and enable the individual Tallyfy tools your team should use (tools are disabled by default).

How Gemini calls Tallyfy

When you ask in plain language, Gemini picks the right Tallyfy tools and runs them:

  • “Find all overdue tasks and create a summary grouped by assignee.” Gemini calls search_for_tasks with an overdue filter, groups by assignee, and writes a summary.
  • “Analyze our customer onboarding processes from the last month and identify bottlenecks.” Gemini queries process history through MCP tools, computes per-step completion times, and surfaces the slowest steps.
  • “Review our Invoice Processing template and suggest improvements.” Gemini fetches the template with get_template, walks the step dependencies and automation rules, and proposes changes.

Because Gemini runs inside Google’s platform, you can combine Tallyfy data with other Google services:

  • BigQuery - analyze Tallyfy process data alongside your data warehouse. For example, correlate support tickets in BigQuery with support process completion times in Tallyfy.
  • Cloud Run - deploy your own MCP logic at scale.
  • Pub/Sub - drive event-based workflow triggers, such as kicking off a document review in Tallyfy when a file lands in Cloud Storage.
  • Vertex AI agents - build multi-agent systems with the Agent Development Kit that combine Tallyfy with other services under Google’s governance controls.

Gemini’s multimodal input also lets it process images and documents alongside text, which helps with visual inspection workflows or document review processes.

Security and authentication

  • Authentication - OAuth 2.1. Gemini CLI and Code Assist register as PKCE public clients through DCR. Gemini Enterprise registers as a confidential client through DCR using client_secret_basic or client_secret_post (both advertised by the server in its /.well-known/oauth-authorization-server metadata). All flows use S256 PKCE for the code challenge. Refresh tokens rotate automatically.
  • Data handling - Google processes your data per their AI policies. Enterprise teams get Vertex AI controls and audit logging in Cloud Logging.
  • Network - All traffic over HTTPS. Enterprise deployments can add VPC Service Controls and private connectivity.

Footnotes

  1. OAuth is the standard that lets you sign in to one app using another account, without sharing your password. ↩

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