Give AI reliable memory across your documents, notes, and meetings
This MCP tool comes from an official registry and has been updated within the last year, which lowers overall concern; however, its closed-source nature, memory/recall use case across documents, notes, and meetings, and outbound connection to api.liminary.io make it a caution-level tool rather than high risk.
The materials explicitly state that no keys or environment variables are required. There is no indication that users must provide API keys, OAuth tokens, or other sensitive credentials, so credential exposure appears limited based on the available facts.
The tool connects to the declared endpoint api.liminary.io. Given the stated use case of recall across documents, notes, and meetings, some user content or retrieval queries may reasonably be sent to the service for processing; however, the endpoint is known and related to the stated function, so this alone does not justify a high-risk rating.
The system checks indicate this tool has executes-code capability, meaning it may start local processes or execute code on the host side. This is a common MCP capability, but the current materials do not document execution boundaries, accessible system capabilities, or sandboxing, so it warrants caution.
The description claims memory and recall across 'documents, notes, and meetings,' indicating expected access to user documents, notes, or meeting-related data. The materials do not specify read/write scope, whether it only indexes data, whether it persists content, or whether it follows least-privilege design, so the actual access scope should be treated with caution.
Positive signals include distribution through an official registry and updates within the last year. However, there is no open-source repository, no declared license, and very low community adoption (0 stars), which limits external auditability and dependency transparency. Overall, the source is not obviously suspicious, but auditability is limited, so caution is appropriate.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "Liminary" MCP server from askskill: Run: claude mcp add --transport http 'io-liminary-api-mcp' 'https://api.liminary.io/api/mcp/'
Search my meeting notes, project notes, and related documents from the last two weeks. Summarize the confirmed key decisions, open questions, and next actions for this project, organized as a timeline.
A project decision recap based on past materials, including confirmed decisions, open issues, and recommended next steps.
Using my documents, notes, and meeting records, answer: Why did we reject option A and choose option B? Include the supporting sources.
A sourced explanation of the historical reasoning process and relevant context.
Extract key points about customer needs from all my relevant materials, deduplicate them, group them by theme, and create a shareable knowledge summary for the team.
A structured knowledge summary that groups scattered information by theme for easier retrieval and collaboration.
Give your AI cross-tool memory with reliable context recall and uncertainty awareness.
Give AI agents persistent memory across sessions with automatic context retrieval.
Give AI coding agents persistent memory across sessions for people, decisions, and context.
Provide deep cross-platform memory so AI retains context and preferences.
Turn meetings and voice notes into a searchable, privacy-first AI memory layer.
Provide persistent memory for AI agents across sessions and tasks.