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skydeckai/mcp-server-rememberizer

skydeckai/mcp-server-rememberizer

An MCP Server to enable global access to Rememberizer
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来源明细
收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
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收录于 2026-10-14 · 最近见到 2026-10-16 · 共见到 4 次 · 被 3 个来源列出
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综合分 303 · 3 个来源 · mcp
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怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
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谁维护它、还在更新吗?
我们收录于 2026-10-14;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

MCP Server Rememberizer

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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.
Components
Resources
The server provides access to two types of resources: Documents or Slack discussions
Tools
1. retrieve_semantically_similar_internal_knowledge
- Send a block of text and retrieve cosine similar matches from your connected Rememberizer personal/team internal knowledge and memory repository
- Input:
- match_this (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
- n_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 information
- from_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 date
- to_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 date
- Returns: Search results as text output
2. smart_search_internal_knowledge
- Search for documents in Rememberizer in its personal/team internal knowledge and memory repository using a simple query that returns the results of an agentic search. The search may include sources such as Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input:
- query (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
- user_context (string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared results
- n_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 information
- from_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 date
- to_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 date
- Returns: Search results as text output
3. list_internal_knowledge_systems
- List the sources of personal/team internal knowledge. These may include Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input: None required
- Returns: List of available integrations
4. rememberizer_account_information
- Get information about your Rememberizer.ai personal/team knowledge repository account. This includes account holder name and email address
- Input: None required
- Returns: Account information details
5. list_personal_team_knowledge_documents
来源
awesome · https://github.com/skydeckai/mcp-server-rememberizer
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