An MCP Server to enable global access to Rememberizer
{
"mcpServers": {
"mcp-server-rememberizer": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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An MCP Server to enable global access to Rememberizer
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
Apache-2.0. View license →
Is it maintained?
Last commit 253 days ago. 35 stars.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
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Persistent memory using a knowledge graph
Privacy-first. MCP is the protocol for tool access. We're the virtualization layer for context.
Pre-build reality check. Scans GitHub, HN, npm, PyPI, Product Hunt — returns 0-100 signal.
Monitor browser logs directly from Cursor and other MCP compatible IDEs.
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A Model Context Protocol server for interacting with Rememberizer's document and knowledge management API. This server enables Large Language Models to search, retrieve, and manage documents and integrations through Rememberizer.
Please note that mcp-server-rememberizer is currently in development and the functionality may be subject to change.
The server provides access to two types of resources: Documents or Slack discussions
retrieve_semantically_similar_internal_knowledge
match_this (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledgen_results (integer, optional): Number of semantically similar chunks of text to return. Use 'n_results=3' for up to 5, and 'n_results=10' for more informationfrom_datetime_ISO8601 (string, optional): Start date in ISO 8601 format with timezone (e.g., 2023-01-01T00:00:00Z). Use this to filter results from a specific dateto_datetime_ISO8601 (string, optional): End date in ISO 8601 format with timezone (e.g., 2024-01-01T00:00:00Z). Use this to filter results until a specific datesmart_search_internal_knowledge
query (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledgeuser_context (string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared resultsn_results (integer, optional): Number of semantically similar chunks of text to return. Use 'n_results=3' for up to 5, and 'n_results=10' for more informationfrom_datetime_ISO8601 (string, optional): Start date in ISO 8601 format with timezone (e.g., 2023-01-01T00:00:00Z). Use this to filter results from a specific dateto_datetime_ISO8601 (string, optional): End date in ISO 8601 format with timezone (e.g., 2024-01-01T00:00:00Z). Use this to filter results until a specific datelist_internal_knowledge_systems
rememberizer_account_information
list_personal_team_knowledge_documents
page (integer, optional): Page number for pagination, starts at 1 (default: 1)page_size (integer, optional): Number of documents per page, range 1-1000 (default: 100)`remember_this