Developer MCP Server

A sophisticated tool for advanced querying and analysis of the software development knowledge graph. This tool provides specialized operations to extract meaningful insights and contextual information from the graph structure. It enables deep exploration of projects, components, relationships, decisions, and progress tracking.

When to use this tool:

• Retrieving the complete development knowledge graph

• Searching for specific entities using keyword or partial matching

• Fetching details on a precise set of development entities

• Exploring all relationships for a specific entity

• Examining the decision history for a software project

• Tracking progress toward project milestones

• Investigating dependencies between components

• Analyzing the evolution of a software project

• Understanding the context surrounding development entities

• Exploring task sequencing and dependencies

• Identifying entities by status or priority

Key features:

• Six specialized query operation types

• Full graph retrieval with entities and relations

• Keyword-based search across entities and their properties

• Direct entity lookup by exact name

• Relationship exploration with filtering options

• Project decision history with chronological ordering

• Milestone progress tracking with task status breakdown

• Status and priority information retrieval

Parameters explained:

• type: The query operation type to perform, which must be one of:

  • "graph" - Retrieve the entire knowledge graph (all entities and relations)

  • "search" - Find entities by keyword/partial match in name, type, or observations

  • "nodes" - Get specific entities by exact name

  • "related" - Get all entities related to a specific entity

  • "decisions" - Get the decision history for a project

  • "milestone" - Get progress tracking for a specific milestone

• params: Operation-specific parameters structure:

  • For "graph": No parameters needed

  • For "search": { query: "search text" }

  • For "nodes": { names: ["EntityName1", "EntityName2", ...] }

  • For "related": { entityName: "EntityName", relationTypes: ["type1", "type2", ...] }

  • For "decisions": { projectName: "ProjectName" }

  • For "milestone": { milestoneName: "MilestoneName" }

Operation details:

• "graph" returns the complete knowledge graph structure

• "search" performs partial matching on entity names, types, and observations

• "nodes" retrieves specific entities by exact name matching

• "related" finds all incoming and outgoing relationships for an entity

• "decisions" retrieves and chronologically sorts project decisions

• "milestone" calculates progress percentage and task breakdowns with status information

Notes:

• Valid status values: "inactive", "active", or "complete"

• Valid priority values: "low" or "high"

• Status is represented via the has_status relation type, and priority via has_priority

Return structures:

• All operations return { success: true/false, ... } with operation-specific data

• Error responses include detailed error messages

• "related" returns both incoming and outgoing relationships

• "milestone" includes progress percentage and task categorization by status

• Sequencing information appears in directed relationship graphs

You should:

1. Select the most appropriate query type for your information need

2. Provide the required parameters for your chosen operation type

3. Start with broader queries and refine to more specific ones

4. Use "search" for exploratory investigation when entity names are unknown

5. Use "related" to explore the neighborhood of a known entity

6. Use "decisions" to understand the rationale behind project changes

7. Use "milestone" to evaluate project progress and identify blockers

8. Analyze task sequencing to understand dependencies and critical paths

9. Filter entities by status to focus on active, inactive, or completed items

10. Consider entity priorities when planning work or resolving issues

11. Combine query results to build comprehensive understanding