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ampcome-mcps

MCP Salesforce Connector

by ampcome-mcps

create_record

Create new Salesforce records by specifying object type and data fields to add information to your CRM database.

Instructions

Creates a new record

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
object_nameYesThe name of the Salesforce object (e.g., 'Account', 'Contact')
dataYesThe data for the new record

Implementation Reference

  • Registers the 'create_record' tool in the list_tools handler, including its name, description, and input schema.
    types.Tool(
        name="create_record",
        description="Creates a new record",
        inputSchema={
            "type": "object",
            "properties": {
                "object_name": {
                    "type": "string",
                    "description": "The name of the Salesforce object (e.g., 'Account', 'Contact')",
                },
                "data": {
                    "type": "object",
                    "description": "The data for the new record",
                    "properties": {},
                    "additionalProperties": True,
                },
            },
            "required": ["object_name", "data"],
        },
    ),
  • Implements the handler logic for 'create_record' tool: validates arguments, connects to Salesforce object, calls create() method, and returns the result as JSON.
    elif name == "create_record":
        object_name = arguments.get("object_name")
        data = arguments.get("data")
        if not object_name or not data:
            raise ValueError("Missing 'object_name' or 'data' argument")
        if not sf_client.sf:
            raise ValueError("Salesforce connection not established.")
        sf_object = getattr(sf_client.sf, object_name)
        results = sf_object.create(data)
        return [
            types.TextContent(
                type="text",
                text=f"Create {object_name} Record Result (JSON):\n{json.dumps(results, indent=2)}",
            )
        ]
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('creates') but doesn't explain what 'creates' entails—such as whether it's a write operation that requires specific permissions, what happens on success/failure, or if there are side effects like triggering workflows. This leaves significant gaps for a mutation tool.

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?

The description is extremely concise with just three words, front-loading the key action ('creates') without any wasted language. Every word earns its place, making it efficient for quick comprehension.

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

Completeness2/5

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

Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address behavioral aspects like permissions, error handling, or return values, which are crucial for safe and effective tool invocation in a context with sibling tools like 'delete_record' and 'update_record'.

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

Parameters3/5

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

The schema description coverage is 100%, so the schema already documents both parameters ('object_name' and 'data') thoroughly. The description adds no additional meaning beyond what the schema provides, such as examples of valid object names or data constraints, which aligns with the baseline score when schema coverage is high.

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

Purpose4/5

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

The description clearly states the verb ('creates') and resource ('new record'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update_record' in terms of when to create versus update, which prevents a perfect score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'update_record' or 'delete_record'. It doesn't mention prerequisites, such as needing valid object names or data structures, leaving the agent to infer usage context from the schema alone.

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

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