Rememberizer
This MCP server, developed by Skydeck AI, provides a bridge between large language models and Rememberizer's document management API. It enables AI assistants to search, retrieve, and manage documents and integrations through semantic similarity queries and LLM agent augmentation. Built in Python, the implementation offers flexible search options, including date filtering and pagination. By connecting AI models with Rememberizer's knowledge base, this server allows AI systems to access and analyze relevant information from various data sources. It is particularly useful for enhancing AI assistants with context-aware responses, supporting research tasks, and enabling more sophisticated document analysis and retrieval in enterprise knowledge management scenarios.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/skydeckai/mcp-server-rememberizer
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Rememberizer from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.