Available MCP Tools
FunnelStory exposes the following tools through the MCP server.
| Tool | What it does |
|---|---|
query_semantic_db | Run SQL queries against your workspace data |
get_flows | List flows or retrieve a specific flow's configuration |
configure_flow | Create or update a flow |
run_flow | Execute a flow and return its output |
configure_data_model | Create or update a data model configuration |
preview_data_model | Preview query results and validate a data model before saving |
read_resource | Read a resource document by URI (guides, schema, workspace profile) |
query_semantic_db
Runs a SQL query against FunnelStory's semantic database — a structured view of your workspace data including accounts, metrics, predictions, activities, meetings, notes, tasks, tickets, and needle movers.
Your AI assistant can read the schema first (available as the file://semantic/schema.sql resource) to understand what tables and columns are available before querying.
Input:
| Field | Type | Description |
|---|---|---|
query | string | SQL query to run |
get_flows
Returns flow metadata for the workspace. Pass a flow_id to get the full configuration of a specific flow — including its trigger, input schema, and graph. Omit it to get a summary list of all flows.
Input:
| Field | Type | Description |
|---|---|---|
flow_id | string | (Optional) ID of the flow to retrieve |
configure_flow
Creates a new flow or updates an existing one. Pass flow_id to update; omit it to create. Flows saved with draft: true won't trigger automatically — useful while you're still building.
Read the file://flow/guide.md resource for the complete flow authoring reference.
Input:
| Field | Type | Description |
|---|---|---|
flow_id | string | (Optional) Flow to update; omit to create |
name | string | Display name |
draft | boolean | If true, saves without publishing |
trigger_config | object | When and how the agent runs — see Triggers |
input_schema | array | Input fields the flow accepts |
config | object | Flow graph with entrypoint and steps |
run_flow
Executes a flow by ID and waits for it to complete. If the flow sets a response variable, that value is returned to the caller.
Input:
| Field | Type | Description |
|---|---|---|
flow_id | string | ID of the flow to run |
input | object | (Optional) Input values, merged with flow defaults |
configure_data_model
Creates or updates a data model in your workspace configuration. Use preview_data_model first to validate the query before saving.
Always read file://data_model/guide.md before calling this tool — it contains the full reference for supported model types, required mappings, and source-specific query patterns (HubSpot, Salesforce, databases).
For HubSpot, always configure models in this order: accounts → users → conversations/notes/activities. The user model must exist before engagement models can resolve account IDs.
Input:
| Field | Type | Description |
|---|---|---|
id | string | (Optional) ID of the model to update. Omit to create a new model. |
name | string | Display name for the model |
type | string | Model type: account, user, conversation, note, support_ticket, non_product_activity, product_activity, etc. |
draft | boolean | If true, saves but does not activate. Defaults to true for new models. |
data_source | object | Query configuration — either data_connection_id + query, or dataset with name and query |
mappings | array | Column-to-property mappings: [{"column": "...", "property": "..."}] |
refresh | object | (Optional) Refresh schedule, e.g. {"interval": "6h"} |
preview_data_model
Validates a data model configuration by running the query and returning a sample of rows with resolved column types. Use this before configure_data_model to confirm the query returns the expected shape and that account_id values match your accounts model.
Input: Same shape as configure_data_model (without id).
read_resource
Reads a reference document by URI and returns its content. Use this to look up guides and schemas before configuring models or flows.
Available resources:
| URI | Contents |
|---|---|
file://data_model/guide.md | Complete guide for configuring data models — model types, required mappings, HubSpot and Salesforce query patterns, configuration order |
file://flow/guide.md | Complete flow authoring reference — triggers, steps, variables, and examples |
file://semantic/schema.sql | Live schema of your workspace's semantic database |
file://semantic/usage.md | How to interpret semantic database tables and values |
file://workspace/profile.json | Your workspace's connected data sources and active models |
Input:
| Field | Type | Description |
|---|---|---|
uri | string | URI of the resource to read |
Next Steps
- Examples — example prompts using these tools
- Getting Started — connect your MCP client
- Configure HubSpot models with Claude — step-by-step walkthrough for HubSpot configuration via MCP
- AI Agents — product concepts, triggers, and examples