Papr
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Last probed Sep 14, 2026 · mcp.papr.ai
8tools discovered
Add Memory
Add a new memory item to Papr Memory API. Args: content: The content of the memory item type: Type of memory (text, code_snippet, document) metadata: Optional metadata for the memory item context: Optional context for the memory item relationships_json: Optional relationships for Graph DB skip_background_processing: Skip background processing if True Returns: Dict containing the added memory item details
Get Memory
Retrieve a memory item by ID. Args: memory_id: The ID of the memory item to retrieve Returns: Dict containing the memory item details
Update Memory
Update an existing memory item. Args: memory_id: The ID of the memory item to update content: New content for the memory item type: New type for the memory item metadata: Updated metadata for the memory item context: Updated context for the memory item relationships_json: Updated relationships for Graph DB Returns: Dict containing the updated memory item details
Delete Memory
Delete a memory item by ID. Args: memory_id: The ID of the memory item to delete skip_parse: Skip Parse Server deletion if True Returns: Dict containing the deletion result
Search Memory
Search through memories with authentication required. Args: query: Detailed search query describing what you're looking for max_memories: Maximum number of memories to return (recommended: 15-20) max_nodes: Maximum number of neo nodes to return (recommended: 10-15) rank_results: Whether to enable additional ranking of search results enable_agentic_graph: Enable agentic graph search for intelligent results user_id: Optional internal user ID to filter search results ex
Submit Feedback
Submit feedback on search results to help improve model performance. Args: search_id: The search_id from SearchResponse that this feedback relates to feedback_type: Type of feedback (thumbs_up, thumbs_down, rating, etc.) feedback_source: Source of feedback (inline, external, etc.) feedback_text: Optional text feedback feedback_score: Optional numerical score feedback_value: Optional feedback value cited_memory_ids: Optional list of cited memory IDs cited_node_ids
Submit Batch Feedback
Submit multiple feedback items in a single request. Args: feedback_items: List of feedback items to submit (max 100) session_context: Optional session-level context for batch feedback Returns: Dict containing the batch feedback submission result
Add Memory Batch
Add multiple memory items in a batch with size validation and background processing. Args: memories: List of memory items to add in batch (max 50) user_id: Internal user ID for all memories in the batch external_user_id: External user ID for all memories in the batch batch_size: Number of items to process in parallel (default: 10) skip_background_processing: Skip background processing if True webhook_url: Optional webhook URL to notify when batch processing is complete
Get your MCP into directories
A working endpoint is step one. Directory coverage is the coordinated launch across ChatGPT, Claude, Cursor, the MCP Registry, and community indexes.
Directory coverage for brandsReplace bloated GTM stacks with customizable AI apps for sales, marketing, and customer workflows. Download Papr Work free for Mac and Windows — community apps, persistent context, and end-to-end automation.
Use the MCP endpoint listed on this page in your MCP client configuration. One-click install pills support Claude, Cursor, VS Code, and other hosts. Copy the remote MCP URL if your client needs a manual entry.
MCPBundles probed 8 tools on the live server. The tool list on this page reflects what was discovered at the last refresh — connect your client to see the full set available to your session.
Papr may require signing in to the provider before tools can run. Connect through MCPBundles or your MCP client and complete any provider login when prompted.
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