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chintanavs

Grid Connect MCP Server

by chintanavs

Grid Connect MCP Server

MCP server for Agentforce Grid (formerly AI Workbench). Enables Claude Code and other MCP clients to create, modify, and monitor Grid workbooks, worksheets, and columns through the Grid Connect API.

Highlights

  • 10 consolidated MCP tools (down from 65) — less tool-selection overhead, faster LLM inference

  • apply_grid — create an entire grid from a single YAML spec (one tool call replaces 10-15 sequential calls)

  • Action-discriminated CRUDworkbook, worksheet, column, cell each handle all operations via an action parameter

  • discover — single tool for all 25 metadata/data/agent discovery queries

  • column — absorbs typed mutations (edit prompt, swap model, add evaluation) as flat parameters alongside raw config

  • Composite workflowssetup_agent_test, poll_worksheet_status, get_worksheet_summary

  • 20 model shorthands including GPT 5.1/5.2, Claude 4.5 Opus, Claude 4.6 Sonnet

  • Hardened request logic with retry on network errors, 429 rate-limit respect, 5xx exponential backoff

Related MCP server: MCP Force

Authentication

This server uses Salesforce CLI (sf) api request commands for all API calls. Authentication is handled entirely by the SF CLI:

  • No manual token management required

  • SF CLI handles OAuth flows, token refresh, and expiration automatically

  • Supports all SF CLI authentication methods (web login, JWT, refresh tokens, etc.)

  • Works with any org authenticated via sf org login

Quick Start

Prerequisites

Install Salesforce CLI:

brew install sf

Setup

  1. Login to your Salesforce org:

sf org login web --alias my-org --instance-url https://your-instance.salesforce.com/

Or set as default org:

sf org login web --set-default --instance-url https://your-instance.salesforce.com/
  1. Verify your connection:

Test that you can access the Grid Connect API:

sf api request rest "/services/data/v66.0/public/grid/workbooks" \
  --method GET \
  --target-org my-org

Or if you set a default org:

sf api request rest "/services/data/v66.0/public/grid/workbooks" \
  --method GET
  1. Install and build:

npm install
npm run build

# Optional: Set environment variables if needed
# export ORG_ALIAS="orgfarm-org"  # If not set, uses SF CLI default org
# export INSTANCE_URL="https://your-instance.salesforce.com"  # Only for Lightning URL generation

npm start

Claude Code Configuration

Minimal configuration (uses SF CLI default org):

{
  "mcpServers": {
    "grid-connect": {
      "command": "node",
      "args": ["/path/to/agentforce-grid-mcp/dist/index.js"]
    }
  }
}

With specific org:

{
  "mcpServers": {
    "grid-connect": {
      "command": "node",
      "args": ["/path/to/agentforce-grid-mcp/dist/index.js"],
      "env": {
        "ORG_ALIAS": "orgfarm-org"
      }
    }
  }
}

Environment Variables

All environment variables are optional:

Variable

Default

Description

ORG_ALIAS

SF CLI default org

Target org alias (if not set, SF CLI uses your default org)

INSTANCE_URL

undefined

Salesforce instance URL (required only for Lightning Experience URL generation via get_url tool)

API_VERSION

v66.0

Salesforce API version

GRID_TIMEOUT

60000

Request timeout in milliseconds

GRID_DEBUG

false

Enable debug logging to stderr

Architecture

src/
  index.ts                    # MCP server entry point
  client.ts                   # SF CLI API wrapper with retry logic
  schemas.ts                  # Zod schemas for all 12 column types
  types.ts                    # Shared types
  tools/
    workbook.ts               # 1 tool: workbook (6 actions: list, create, create_with_worksheet, get, get_worksheets, delete)
    worksheet.ts              # 1 tool: worksheet (11 actions: create, get, get_data, update, delete, add_rows, etc.)
    column.ts                 # 1 tool: column (15+ actions: CRUD + typed mutations like edit_ai_prompt, change_model)
    cell.ts                   # 1 tool: cell (5 actions: update, paste, trigger_execution, validate_formula, generate_ia_input)
    discover.ts               # 1 tool: discover (25 actions: all metadata, data, agent discovery)
    workflows.ts              # 3 tools: setup_agent_test, poll_worksheet_status, get_worksheet_summary
    apply-grid.ts             # 1 tool: apply_grid (YAML DSL → entire grid in one call)
    urls.ts                   # 1 tool: get_url (Lightning Experience URLs)
  lib/
    yaml-parser.ts            # Parse YAML DSL → GridSpec AST
    validator.ts              # 6-pass semantic validation (refs, cycles, types)
    config-expander.ts        # Flat YAML → triple-nested GCC JSON (Zod-validated)
    resolution-engine.ts      # Full pipeline: parse → validate → sort → create
    model-map.ts              # Model shorthand ↔ sfdc_ai__ ID mapping (20 shorthands)
    config-helpers.ts         # Shared: fetch config, resolve refs, deep merge
    column-config-cache.ts    # Session-lifetime config cache for typed mutations
    worksheet-data-helpers.ts # Helpers for columnData response format
    resource-cache.ts         # TTL-based cache for MCP resources

Tool Categories

apply_grid — Declarative Grid Creation

The flagship tool. Pass a YAML spec and get a complete grid:

workbook: Sales Agent Tests
worksheet: Q1 Regression
columns:
  - name: Utterances
    type: text

  - name: Agent Output
    type: agent_test
    agent: "Sales Coach"
    inputUtterance: "Utterances"

  - name: Coherence
    type: eval/coherence
    input: "Agent Output"

  - name: Topic Check
    type: eval/topic_assertion
    input: "Agent Output"
    reference: "Expected Topics"

data:
  Utterances:
    - "How do I reset my password?"
    - "What is my account balance?"

The tool handles:

  • Workbook/worksheet creation

  • Agent name → ID resolution

  • Column dependency ordering (topological sort)

  • Config expansion (flat YAML → nested JSON validated by Zod)

  • Sequential column creation with ID wiring

  • Data population

  • dryRun mode for validation without API calls

Typed Mutation Tools

Modify existing grids without constructing raw JSON:

Tool

Purpose

edit_ai_prompt

Change instruction, model, response format on AI columns

edit_agent_config

Update agent, utterance, context variables

add_evaluation

Add evaluation column with auto-wired references

change_model

Switch LLM model (supports shorthands like gpt-4-omni, claude-4.5-sonnet)

update_filters

Change Object/DataModelObject query filters

reprocess

Reprocess column or worksheet (all/failed/stale)

edit_prompt_template

Update template and input mappings

CRUD Tools

Standard operations for workbooks, worksheets, columns, cells, rows.

Discovery Tools

Tool

Returns

get_agents

Available agents with IDs, versions, topics

get_llm_models

Available models

get_evaluation_types

All 12 evaluation types

get_sobjects / get_sobject_fields

SObject metadata

get_dataspaces / get_data_model_objects

Data Cloud DMOs

get_prompt_templates

Available prompt templates

get_invocable_actions

Available Flows, Apex, etc.

get_formula_functions / get_formula_operators

Formula reference

Composite Workflows

Tool

Purpose

setup_agent_test

Create a full agent test suite in one call

poll_worksheet_status

Poll until processing completes

get_worksheet_summary

Structured column/status summary

create_workbook_with_worksheet

Create both in one step

Column Types

All 12 Agentforce Grid column types are supported with typed Zod schemas:

Type

DSL Name

Purpose

AI

ai

LLM text generation with custom prompts

Agent

agent

Run agent conversations

AgentTest

agent_test

Batch agent testing

Object

object

Query Salesforce SObjects

DataModelObject

data_model_object

Query Data Cloud DMOs

Evaluation

eval/*

Evaluate outputs (12 evaluation types)

Reference

reference

Extract fields via JSON path

Formula

formula

Computed values

PromptTemplate

prompt_template

Execute prompt templates

InvocableAction

invocable_action

Execute Flows/Apex

Action

action

Standard platform actions

Text

text

Static/editable text

Model Shorthands

Use short names instead of full sfdc_ai__* identifiers:

Shorthand

Model

gpt-4-omni

GPT 4 Omni

gpt-4-omni-mini

GPT 4 Omni Mini

gpt-4.1

GPT 4.1

gpt-4.1-mini

GPT 4.1 Mini

gpt-5

GPT 5

gpt-5-mini

GPT 5 Mini

o3

O3

o4-mini

O4 Mini

claude-4.5-sonnet

Claude 4.5 Sonnet

claude-4.5-haiku

Claude 4.5 Haiku

claude-4-sonnet

Claude 4 Sonnet

gemini-2.5-flash

Gemini 2.5 Flash

gemini-2.5-flash-lite

Gemini 2.5 Flash Lite

gemini-2.5-pro

Gemini 2.5 Pro

nova-lite

Amazon Nova Lite

nova-pro

Amazon Nova Pro

Validation

Every column config is validated against typed Zod schemas before hitting the API. The apply_grid tool adds 6-pass semantic validation:

  1. Schema — required fields, valid types

  2. Type-specific fields — each column type's required config

  3. Reference integrity — all column name references resolve

  4. Cycle detection — no circular dependencies (Kahn's algorithm)

  5. Type compatibility — eval targets valid column types

  6. Value validation — valid eval types, model names, response formats

Development

npm run build    # Compile TypeScript
npm run dev      # Watch mode
npm start        # Run the server
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Response time
Release cycle
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