Skip to main content
Glama

clear_project_context

Reset to organization-level scope by clearing the current project context in Azure DevOps.

Instructions

Clears the project context, reverting to organization-level scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function that implements the tool logic by clearing the project_context attribute on the client instance and returning a success message.
    def clear_project_context(self):
        self.project_context = None
        return {"message": "Project context cleared."}
  • The tool registration in the server's tools list, including name, description, and empty input schema since no parameters are required.
    types.Tool(
        name="clear_project_context",
        description="Clears the project context, reverting to organization-level scope.",
        inputSchema={
            "type": "object",
            "properties": {},
            "additionalProperties": False
        }
    ),
  • The dispatch handler in the server's _execute_tool method that routes the tool call to the client's clear_project_context method.
    elif name == "clear_project_context":
        return self.client.clear_project_context()
  • The input schema definition for the tool, specifying an empty object with no properties required.
    inputSchema={
        "type": "object",
        "properties": {},
        "additionalProperties": False
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the tool 'Clears the project context,' which implies a mutation or state change, but doesn't disclose behavioral traits such as whether this requires specific permissions, if it's reversible, or what side effects occur. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence that front-loads the core action and outcome with zero waste. Every word earns its place, making it highly concise and well-structured.

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

Completeness3/5

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

Given the tool has 0 parameters, no annotations, and no output schema, the description is minimal but covers the basic purpose. However, for a mutation tool that changes context state, it lacks details on permissions, reversibility, or error conditions, making it incomplete for safe and effective use by an AI agent.

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?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add param details beyond the schema, but with no parameters, a baseline of 4 is appropriate as it adequately covers the absence of inputs.

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 action ('Clears') and the resource ('project context'), with the outcome specified ('reverting to organization-level scope'). It distinguishes from siblings like 'set_project_context' by indicating a reversal. However, it doesn't explicitly differentiate from other context-related tools, 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 Guidelines3/5

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

The description implies usage when reverting from project-level to organization-level scope, but it doesn't explicitly state when to use this tool versus alternatives (e.g., after using 'set_project_context') or provide exclusions. The context is clear but lacks explicit guidance on when-not-to-use or named alternatives.

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/xrmghost/mcp-azure-devops'

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