Retrieve DoorDash store fulfillment methods, delivery fee info, and scheduling details from a store ID and delivery location. No account or token required.
MIT
520,104 tools. Updated 2026-09-06 09:13
"Methods to Store and Learn Dynamic Context Memories" matching MCP tools:
- Store important facts, decisions, user preferences, and project context for long-term retrieval. Memories persist across sessions with automatic chunking and duplicate detection.MIT
- Save key-value pairs to persistent memory across sessions for remembering user preferences, installed skills, or project context.MIT
- Explain a type's fields and its role in methods (construct, mutate, consume, destroy) from graph facts. Learn a struct's shape and handling before reading call sites.AGPL 3.0
- Retrieve saved memories at session start to restore context, installed skills, and user preferences. Filter by type for specific categories.MIT
- Store observations as persistent memories with optional tags, importance levels, context, and auto-expiration to manage AI agent memory.MIT
Matching MCP Servers
- AlicenseAqualityDmaintenanceA Model Context Protocol (MCP) server that injects 'Just-in-Time' context into AI conversations based on file paths and glob patterns.1231ISC
- AlicenseAqualityCmaintenanceEnables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.8MIT
Matching MCP Connectors
Official Microsoft Learn MCP Server – real-time, trusted docs & code samples for AI and LLMs.
- Era ContextOAuth
Personal finance, bank account, and shared memory connector for Claude, ChatGPT, Gemini Spark & more
- Process raw conversation messages to automatically extract and store useful memories, facts, decisions, preferences, and lessons.MIT
- Retrieve relevant memories for user queries to fetch prior context, preferences, and facts before responding.MIT
- List all stored memories for the current user from both Arc and Atlas in the shared store.MIT
- Extract and store important information from conversations to maintain persistent memory across interactions, enabling AI assistants to recall facts and user context.MIT
- Retrieve project context at session start: recent memories and an AI summary covering architecture, tech stack, and patterns. Use this to avoid manual memory recall.MIT
- Retrieve data from Aspro.Cloud using list and get methods. Run aspro_describe first to learn parameters, then pass entity id and query arguments to get status, URL, and data.MIT
- Retrieve aggregate counts of stored memories and session events for monitoring. Check store health or confirm data was saved after a session.MIT
- Persist key information as memories in a local database for cross-session use. Record preferences, lessons, project context, and relationship notes to be recalled later.MIT
- Retrieve paginated memories from an agent's archival store with search, sorting, and filtering capabilities.MIT
- Store key decisions, insights, or notes in a private memory wiki that auto-titles, tags, and links them to related memories for easy future recall.MIT
- Store new memories to retain novel insights, decisions, and debugging solutions across sessions. Automatically rejects near-duplicates to avoid clutter.Apache 2.0
- Retrieve relevant memories from past sessions to provide context for current queries. Returns diverse, re-ranked results so similar memories don't crowd out distinct ones.AGPL 3.0
- Gather the most reflection-worthy memories by importance and recency, then synthesize and store higher-level insights linked to their source memories.PolyForm Noncommercial 1.0.0
- Starting a project? Retrieve relevant memories from its path and return a compressed summary to restore working context.MIT
- Retrieve stored memories from an encrypted memory store. Enter a keyword to filter results, or leave empty to load all past context at session start.Apache 2.0