Documentation Index Fetch the complete documentation index at: https://mintlify.com/Nectr-AI/nectr-ai-pr-review-agent/llms.txt
Use this file to discover all available pages before exploring further.
Overview List all Mem0 AI memories for a specific repository. Memories capture project context, developer patterns, coding standards, and architectural decisions learned from analyzing PRs.
Authentication Requires a valid JWT token in the Authorization header:
Authorization: Bearer YOUR_JWT_TOKEN
Query Parameters Repository to query in owner/repo format (e.g., “acme/api-server”)
Filter by memory type. Valid values:
project_rule: Project-specific guidelines and standardscontributor_profile: Developer contribution summariesdeveloper_pattern: Individual coding patterns and habitsdeveloper_strength: Technical areas of expertisearchitecture: System architecture and design decisionsproject_map: Codebase structure and module descriptions Response Memory content (text description)
Additional metadata about the memory
memories[].metadata.memory_type
Type of memory (project_rule, contributor_profile, etc.)
memories[].metadata.username
Associated GitHub username (for developer-specific memories)
memories[].metadata.source_pr
PR number where this memory was learned
memories[].metadata.pr_count
Number of PRs analyzed (for contributor profiles)
memories[].metadata.commit_count
Total commits (for contributor profiles)
Total number of memories returned
Example Request cURL
cURL (Filtered)
Python
JavaScript
curl -X GET "https://api.nectr.ai/api/v1/memory?repo=acme/api-server" \ -H "Authorization: Bearer YOUR_JWT_TOKEN"
Example Response { "memories" : [ { "id" : "mem_a1b2c3d4e5" , "memory" : "All API endpoints must include comprehensive error handling with custom exception classes that inherit from BaseAPIException." , "metadata" : { "memory_type" : "project_rule" , "source_pr" : 42 , "repo" : "acme/api-server" } }, { "id" : "mem_f6g7h8i9j0" , "memory" : "Database migrations must include both upgrade and downgrade scripts. Never modify existing migrations." , "metadata" : { "memory_type" : "project_rule" , "source_pr" : 38 , "repo" : "acme/api-server" } }, { "id" : "mem_k1l2m3n4o5" , "memory" : "Experienced backend developer focused on API design. Consistently delivers well-tested code with comprehensive documentation." , "metadata" : { "memory_type" : "contributor_profile" , "username" : "johndoe" , "pr_count" : 47 , "commit_count" : 312 , "repo" : "acme/api-server" } }, { "id" : "mem_p6q7r8s9t0" , "memory" : "Prefers async/await patterns for all database operations. Always uses SQLAlchemy async session management." , "metadata" : { "memory_type" : "developer_pattern" , "username" : "johndoe" , "source_pr" : 45 , "repo" : "acme/api-server" } } ], "count" : 4 }
Memory Types project_rule Project-specific coding standards, architectural guidelines, and best practices that all contributors should follow.
Example: "All authentication endpoints must use JWT tokens with 15-minute expiration and refresh token rotation."
contributor_profile High-level summary of a developer’s contribution style and expertise, generated from analyzing their PR history.
Example: "Senior frontend engineer specializing in React and TypeScript. Known for creating accessible, performant user interfaces."
developer_pattern Specific coding patterns, habits, and preferences identified for individual developers.
Example: "Favors functional React components with custom hooks. Always implements comprehensive unit tests using React Testing Library."
developer_strength Technical areas where a developer demonstrates expertise.
Example: "Database schema design and query optimization. Expert in PostgreSQL performance tuning."
architecture High-level system architecture decisions and design patterns used in the codebase.
Example: "Microservices architecture with event-driven communication using RabbitMQ. Each service has independent database."
project_map Codebase structure, module descriptions, and file organization patterns.
Example: "app/api/v1/ contains all REST API endpoints organized by resource type (users, reviews, analytics)."
Error Responses Repository Not Connected { "detail" : "Repo not connected or access denied" }
HTTP Status: 403 Forbidden
Use Cases Display Project Rules data = list_memories( repo = "acme/api-server" , memory_type = "project_rule" ) print ( "📋 Project Coding Standards:" ) for i, memory in enumerate (data[ 'memories' ], 1 ): print ( f " { i } . { memory[ 'memory' ] } " ) if 'source_pr' in memory[ 'metadata' ]: print ( f " (Learned from PR # { memory[ 'metadata' ][ 'source_pr' ] } )" )
Developer Onboarding def generate_onboarding_guide ( repo ): # Get project structure project_map = list_memories( repo = repo, memory_type = "project_map" ) # Get coding standards rules = list_memories( repo = repo, memory_type = "project_rule" ) # Get architecture overview architecture = list_memories( repo = repo, memory_type = "architecture" ) guide = "# Developer Onboarding Guide \n\n " guide += "## Project Structure \n " for mem in project_map[ 'memories' ]: guide += f "- { mem[ 'memory' ] } \n " guide += " \n ## Architecture \n " for mem in architecture[ 'memories' ]: guide += f "- { mem[ 'memory' ] } \n " guide += " \n ## Coding Standards \n " for mem in rules[ 'memories' ]: guide += f "- { mem[ 'memory' ] } \n " return guide
Context for AI Code Review def get_review_context ( repo ): """Build context for AI reviewer from memories.""" rules = list_memories( repo = repo, memory_type = "project_rule" ) architecture = list_memories( repo = repo, memory_type = "architecture" ) context = "Project Context: \n\n " context += "Coding Standards: \n " for mem in rules[ 'memories' ]: context += f "- { mem[ 'memory' ] } \n " context += " \n Architecture: \n " for mem in architecture[ 'memories' ]: context += f "- { mem[ 'memory' ] } \n " return context
Team Knowledge Base from collections import defaultdict data = list_memories( repo = "acme/api-server" ) by_type = defaultdict( list ) for memory in data[ 'memories' ]: memory_type = memory[ 'metadata' ].get( 'memory_type' , 'unknown' ) by_type[memory_type].append(memory) print ( "📚 Team Knowledge Base \n " ) for memory_type, memories in by_type.items(): print ( f "## { memory_type.replace( '_' , ' ' ).title() } ( { len (memories) } )" ) for mem in memories[: 3 ]: print ( f " - { mem[ 'memory' ][: 100 ] } ..." ) print ()