Salesforce AI Agent MCP Server

salesforce_deploy_metadata

Deploy Salesforce metadata by uploading a base64-encoded ZIP package. Configure test execution, check-only validation, and rollback behavior.

Instructions

Trigger a Salesforce metadata deployment using the Metadata API. The metadata must be provided as a base64-encoded ZIP file containing a standard Salesforce metadata package.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "zipFile": "<zipFile>"
    },
    "name": "salesforce_deploy_metadata"
  }
}

Input Schema

Name	Required	Description	Default
`zipFile`	Yes	Base64-encoded ZIP file containing the Salesforce metadata package. Must include package.xml and the appropriate metadata folders.
`runTests`	No	Specific test class names to run when testLevel is 'RunSpecifiedTests'
`checkOnly`	No	If true, validates the deployment without making changes (dry run). Default false.
`testLevel`	No	Test execution level. Use 'RunLocalTests' or 'RunAllTestsInOrg' for production deployments.	NoTestRun
`ignoreWarnings`	No	Allow deployment to succeed with warnings (default false)
`rollbackOnError`	No	Roll back all changes if any component fails (default true)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 9, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It fails to mention that deployments are typically asynchronous, that a deployment ID is returned, or that changes may be rolled back if errors occur. It also doesn't state potential side effects beyond the obvious deployment action, which is a significant gap for a mutating operation.

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 a single concise sentence, front-loaded with the core action and requirement. No filler or redundant information, earning a high score for efficiency.

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?

Despite having 6 parameters, no annotations, no output schema, and a sibling for status checking, the description is minimal. It doesn't explain the deployment workflow, what the tool returns, or how to leverage the result. This is insufficient for the complexity and mutating nature of the operation.

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?

Schema description coverage is 100%, so parameters are already well-documented. The description adds no additional meaning beyond restating the ZIP requirement, which is already present in the schema. Baseline 3 is appropriate.

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?

The description clearly states the tool triggers a Salesforce metadata deployment via the Metadata API, with a specific requirement for a base64-encoded ZIP. This distinguishes it from sibling tools like salesforce_get_deployment_status and jira_get_story.

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?

No guidance is provided on when to use this tool versus alternatives such as salesforce_get_deployment_status. The description doesn't mention the deployment lifecycle or that users may need to check status separately, leaving the agent to infer usage context.

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

Deploy Server