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get_project_context

Retrieve project context for AI assistants using the Model Context Protocol (MCP), enabling seamless integration with Buildable projects for task management and progress tracking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP server tool registration and handler for 'get_project_context'. Fetches project context using the BuildableMCPClient and returns it formatted as MCP content.
    this.server.tool('get_project_context', {}, async () => {
      if (!this.client) {
        throw new Error('Not connected to Buildable API');
      }
    
      const context = await this.client.getProjectContext();
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(context, null, 2),
          },
        ],
      };
    });
  • BuildableMCPClient method that performs the actual API request to retrieve the project context from the Buildable API.
    async getProjectContext(): Promise<ProjectContext> {
      this.log('debug', 'Fetching project context...');
    
      try {
        const response = await this.makeRequest<ProjectContext>(
          'GET',
          `/projects/${this.config.projectId}/context`
        );
    
        this.log('info', 'Successfully retrieved project context');
        return response.data!;
      } catch (error) {
        this.log('error', 'Failed to get project context:', error);
        throw error;
      }
    }
  • TypeScript interface defining the structure of the ProjectContext returned by the tool.
    export interface ProjectContext {
      project: {
        id: string;
        title: string;
        description: string;
        status: 'planning' | 'in_progress' | 'completed' | 'paused';
        created_at: string;
        updated_at: string;
      };
      plan: {
        overview: string;
        technology_stack: string[];
        architecture: string;
        timeline: string;
        requirements: string[];
        technical_specifications: string;
      };
      tasks: {
        total: number;
        completed: number;
        in_progress: number;
        pending: number;
        summary: TaskSummary[];
      };
      context: {
        recent_activity: string[];
        current_phase: string;
        next_priorities: string[];
      };
    }
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

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

Completeness1/5

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

Tool has no description.

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

Parameters1/5

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

Tool has no description.

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

Purpose1/5

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

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

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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