Skip to main content
Glama
Coalesce-Software-Inc

coalesce-transform-mcp

Official

Build Pipeline from Intent

build_pipeline_from_intent

Translate natural language pipeline descriptions into executable Coalesce pipeline nodes by parsing intent, matching entities, and selecting node types.

Instructions

Build a Coalesce pipeline from a natural language description. Describe what you want in plain English and this tool resolves workspace nodes, selects node types, and creates the pipeline nodes.

Examples:

  • "combine customers and orders by customer_id, aggregate total revenue by region"

  • "stage the raw payments table"

  • "join products with inventory on product_id"

The tool parses the intent, fuzzy-matches entity names to existing workspace nodes, and selects appropriate node types. When confirmed, it creates the pipeline nodes directly. Alternatively, set dryRun=true to get the plan without creating nodes, then pass it to create_pipeline_from_plan.

If entity names cannot be resolved or the intent is ambiguous, the tool returns clarification questions instead of a plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNoWhen true, return the generated plan without creating nodes.
intentYesNatural language description of the pipeline to build. Mention table/node names, join keys, aggregations, and filters.
schemaNoOptional target schema
databaseNoOptional target database
repoPathNoOptional local committed Coalesce repo path for repo-first node-type ranking. Falls back to COALESCE_REPO_PATH or `repoPath` in the active ~/.coa/config profile when omitted.
confirmedNoSet to true only after presenting the plan to the user and receiving explicit approval.
targetNameNoOptional target node name override
workspaceIDYesThe workspace ID
locationNameNoOptional target locationName
targetNodeTypeNoOptional node type override. When omitted, the planner selects the best type automatically.
confirmationTokenNoThe token returned in the STOP_AND_CONFIRM response. Required when confirmed=true.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
planNo
errorNo
dryRunNo
reasonNo
createdNo
warningNo
cancelledNo
nodeCountNo
incompleteNo
workspaceIDNo
createdNodesNo
cleanupFailuresNo
STOP_AND_CONFIRMNo
failedPlanNodeIDNo
cleanupFailedNodeIDsNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses key behaviors: parses intent, fuzzy-matches entities, selects node types, creates nodes upon confirmation, returns clarification questions when ambiguous. Annotations indicate write operation (readOnlyHint=false) and non-destructive, consistent with description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with examples, clear flow, and no redundant sentences. Every sentence adds value, including the crucial note about STOP_AND_CONFIRM response. Front-loaded with main purpose and alternatives.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given tool complexity (11 parameters, requires output schema which exists), description fully explains workflow, error handling (ambiguity), and integration with confirmation. No gaps identified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers all parameters (100% coverage), but description adds meaningful context: explains dryRun returns plan without creation, confirmed requires confirmationToken, repoPath fallback behavior, and targetNodeType auto-selection. This extra context justifies above baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool builds a Coalesce pipeline from natural language, with specific verb 'build', resource 'pipeline', and source 'intent'. Distinguishes from sibling 'create_pipeline_from_plan' by mentioning it as an alternative for dry-run plans.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: when to use (natural language intent), when to use dryRun, prerequisite of workspaceID and intent, required confirmation flow with confirmationToken, and fallback to clarification questions for ambiguity. Also mentions alternative tool create_pipeline_from_plan.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Coalesce-Software-Inc/coalesce-transform-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server