Skip to main content
Glama
619,831 tools. Updated 2026-09-28 18:53

"Information on memory" matching MCP tools:

  • CALL THIS FIRST, before working in a memory — it is the briefing. One composite read that answers what a cold agent actually needs: what this memory holds (classes and counts), what landed recently, where the memory contradicts itself, how much is waiting for a human's approval, and the newest session checkpoint — where the last session stopped. `memory` is the slug from list_my_memories. `topic` additionally runs the hybrid search and inlines the hits, so "brief me, and specifically about pricing" is one call rather than two. `limit` bounds the recent list. Read the `status` on everything it returns: 'unapproved' rows are proposals a human has not accepted, and saying so is the difference between reporting the team's record and inventing it — `review_queue` counts how many are waiting, and a person clears them in the review UI. `conflicts` are places the memory disagrees with itself — surface them, don't pick a side. Reach for something else when you already know what you are looking for: semantic_search for a topic, get_object for one thing, list_objects for a population.
    ConnectorAPI key
  • Fetch the AI-maintained memory document for a project or workspace — the best single source for a handoff-style briefing. Sections include purpose, glossary, key people, activity digest, and routing signals, distilled across all meetings. Pass EXACTLY ONE of `project_id` (project memory) or `workspace_id` (workspace-level memory); get ids from `list_workspaces`. Returns the memory as rendered markdown plus `updated_at`. Start here for "give me a summary / bring me up to speed on project X" questions, then drill into `find_subjects`/`search_meeting_transcripts` for specifics.
    ConnectorOAuth
  • Permanently delete one memory by UUID. When to use: user asks to remove outdated or incorrect context, or to free plan storage. When NOT: fix content → update (mode=replace); find the ID first → list_memories or recall. Requires delete OAuth scope. Non-idempotent: deleting the same memory_id twice fails. Errors: Memory not found, Not authorized to delete this memory. Side effects: removes the memory row and vector embedding with no recovery; invalidates plan cache. The target workspace is always the one the memory itself belongs to (echoed in resolved_workspace); optionally pass workspace: <name> as a safety confirmation — the call fails if the memory is not actually in that workspace.
    Connector
    Destructive
    No auth
  • Update an existing memory by ID. Use mode replace (default) to patch fields, or append to extend content. Re-embeds only when content changes. The target workspace is always the one the memory itself belongs to (echoed in resolved_workspace); optionally pass workspace: <name> as a safety confirmation — the call fails if the memory is not actually in that workspace.
    ConnectorNo auth
  • IMPORTANT — bulk domain migration: domain moves via revise are for individual corrections only. If the user needs to move many memories between domains, inform the user that bulk migration must be performed via the admin interface (merge_domains) — do not attempt to replicate a merge by looping revise calls. Update one or more existing memories. Omitted fields are unchanged. Single: pass fields directly — returns {updated, connections, suggested_connections} and, when the filing-time threshold is crossed, possible_contradicts + possible_contradicts_candidates (same shapes as remember()). Batch: {items:[{id,...},...]} — returns {items:[{id, updated, connections, suggested_connections, ...}]} with a per-item envelope on each success, not only an updated count. After every successful revise — plain update, override, claim, or supersede — review connections, suggested_connections, and possible_contradicts in the same turn; do not defer to a separate recall or suggest_connections call. Semantic similarity reflects aboutness, not agreement; the server surfaces candidates that may warrant your review but never asserts they conflict. Every memory has an owner (whoever created it) — revising a memory you don't own is rejected with error_class=forbidden unless you are an Editor or Owner and supply override_reason (required) plus override_confirm=true (required only when the memory is human-owned; not required for agent-owned or ownerless memories). The override path requires a session with a workspace role (a human JWT session, or a personal key linked to an Editor/Owner user); sessions on plain workspace keys cannot override regardless of arguments. An override changes content in-place, not ownership — substantive changes (label, description, why_matters, node_kind) on a foreign-owned memory are rejected; use supersede=true instead, which creates your successor memory, archives the original intact, and wires a supersedes relationship. supersede=true (single-memory form only) returns {superseded, archived_id, archived_connections} plus the revise envelope on the successor; foreign supersede uses the same override_reason/override_confirm ceremony. Correction-class overrides (tags, occurred_at, transient) may still use in-place override. override_reason/override_confirm/supersede apply to the single-memory form only — batch revise has no override or supersede path: if any item in the batch targets a memory you don't own, the whole batch is rejected and none of it applies; revise that item individually instead. claim=true (single-memory form only) makes an ownerless memory (owner_id IS NULL — either it predates ownership tracking, or was orphaned by a member offboard) yours: requires Editor or Owner role, is rejected with error_class=validation if the memory already has an owner (use override or supersede instead), and error_class=conflict if someone else claimed it first (race). claim never moves a memory from one owner to another — only from no owner to you — and may be combined with other field updates in the same call. domain (single-memory form only) moves the memory to a different domain; domain_move_reason is required when domain is present — the call is rejected with error_class=validation if domain_move_reason is absent; domain equal to the memory's current domain is also rejected. On failure, content[0].text is JSON: {"error_class": "not_found|conflict|retryable|forbidden|validation|internal", "message": "..."}. Switch on error_class: retry on retryable, surface message on validation, re-fetch on not_found.
    ConnectorAPI key
  • Agent Brain — Reason over a question or task with your agent's own persistent memory in the loop: recalls up to 12 relevant memories from your agent's private scope, reasons with Claude, and writes up to 3 new memories back, so the agent improves with every call. Recall by meaning, not just keyword, when the estate's memory server is reachable (falls back to its own always-on store otherwise — never fails the call). Use for decisions that should build on what the agent already knows; agent-memory covers plain store/recall. Runs claude-haiku-4.5 — the response names the model that served the call; agent-brain-smart runs the identical contract on claude-sonnet-5. Input: {think: string}. Returns {answer, reasoning, confidence, memories_considered, used_memories, learned, model, engine}. (8 MESH/call, a tool · cognition)
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    A
    quality
    A
    maintenance
    A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.
    6
    15
    660 npm
    5
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.
    7
    10 npm
    8
    Apache 2.0

Matching MCP Connectors

  • [ChatGPT Connector compat] Fetch memory by ID. Exists to satisfy ChatGPT Deep Research's required `search`/`fetch` tool contract. Native MCP clients should fetch via `recall` + memory_id, or use the API's GET /memories/{id} endpoint directly. Returns a single memory with citation support (id, title, url, text fields). Args: id: Memory UUID to fetch ctx: MCP context Returns: Dict with id, title, url, text, metadata fields
    ConnectorOAuth
  • Get information about Follow On Tours — who we are, what we sell (bespoke cricket and golf travel), our experience, our financial protection, and how the service works. Use this when someone asks who Follow On Tours is, whether they cover a sport or destination, or how the service operates.
    ConnectorNo auth
  • Get information about Follow On Tours — who we are, what we sell (bespoke cricket and golf travel), our experience, our financial protection, and how the service works. Use this when someone asks who Follow On Tours is, whether they cover a sport or destination, or how the service operates.
    ConnectorNo auth
  • Real-time web search via Tavily for current events, fact-checking, and research. Use search_depth='advanced' for complex queries (higher quality, higher cost) and topic='news' or 'finance' for headlines or market information. Use when: Choose when the task needs current, external, or factual information not available from on-chain or local data — e.g. news, prices, documentation, or fact-checking. Limitations: Returns web snippets, not raw page bodies; results depend on Tavily coverage. Advanced depth costs more. Not a substitute for on-chain tools like get_token_price. Alternatives: get_token_price, http_fetch
    ConnectorNo auth
  • Manage an existing memory item. Currently supports deleting a memory by id (soft delete — recoverable for 30 days). Use search_memory to find the id first.
    Connector
    Destructive
    No auth
  • The knowledge base's own log file, plus when the data was actually ingested. Use `bundleGenerated` to answer "how current is this" or to cite a version — the `generated` field on get_stats is when this server built its in-memory index and changes on every restart, which is a fact about the process rather than the data.
    ConnectorNo auth
  • List running processes on an agent-managed device — live read via the agent tunnel. Wraps POST /api/getDeviceProcesses (permission: devices). Returns rows as reported by GETPS: (process id, name, parent, memory, etc. — exact shape depends on the agent version). Common diagnostic patterns: pair with agent_services to answer 'is the SQL Server service running but stuck?'; correlate top memory/cpu processes with eventlog_search criticals. Read-only by design — the process-kill endpoint (KILLPS) is deliberately NOT exposed via mcpmond. Server-side timeout is 60s; expect 400 if the device is offline or not enrolled. Example: agent_processes({device_id: 42})
    ConnectorNo auth
  • Append a block to the calling user's persistent agent memory. Use this when the user explicitly says "remember X", "save this", or "note for next time" — DO NOT auto-update on every interaction. Memory is auto-prepended to your system prompt on every chat in this user's account. Cap: 10240 bytes total; over-cap appends return 413. Markdown is encouraged; keep entries terse and factual (preferences, project context, references), not verbose.
    ConnectorOAuth
  • Return the memory database's tables, columns, and types. Use this when a SQL query needs the schema first. Do not use it to read stored content; it describes structure alone. Read-only and cheap. The schema itself is public information; the data in those tables stays protected by RLS. Returns: Every table with its columns and their types.
    ConnectorOAuth
  • Detailed property information by property ID — beds, baths, sqft, year built, lot size, tax assessment, HOA, days on market, photos, last sale price/date. Use for_sale search first to get property_id (RapidAPI / Realtor.com data)
    ConnectorNo auth
  • Create or query data in an AiAkiv app. Use this when the user asks to make or look up something in an AiAkiv app, for example a card built from a memory they already have, or to manage their AiAkiv account through the `console` app: teams and invitations, org links, audit logs, save-target history, switching Main or turning it off and on, project presets, and the cards they created. Do not use it to save a memory; use `save_memory` for that. Writes when `action="create"`. Some apps publish the result to the open web: the returned link is live the moment it comes back — unlisted, but reachable by anyone holding the address — and that publication cannot be undone from here. The content is written by the caller from memory the user can already read; the server never calls a model. Args: app: The app name. An unknown one returns `available_apps`. action: `"describe"` returns the app's field list and limits, which is how the exact input shape for an app is established; `"create"` writes. Apps may define further read actions, which `describe` lists. data: The app's payload — a JSON object, or a JSON string holding one. The string form survives transports that mangle long multi-line fields. Returns: `{ok, app, key, url, notice?}` on create, or `{error, hint}`. The returned `url` is the link to the created item. A `notice` is the app stating what just became public and how to undo it, which is information the user needs to see rather than a detail to compress away. On a shape error the app names the offending field.
    Connector
    Destructive
    OAuth
  • Get detailed profile information for a specific funder. Polymorphic identifier — pass ``ein`` for US 990 foundations OR ``funder_id`` (bare UUID / ``n9f:<uuid>``) for non-990 funders such as European, UK 360Giving, and Canadian CRA T3010 funders. ``search_funders`` returns both fields on every hit, so the caller can hand either one back here. At least one identifier must be supplied. Use this after searching for funders to get detailed information about a specific one.
    ConnectorNo auth
  • Get aggregate statistics about missions on the HomeVisto platform. Returns total counts, status breakdown, and average bounty information. Useful for understanding platform activity.
    ConnectorNo auth
  • Semantic-only vector search over the memory, returning source excerpts. Prefer cortex_ask, which also uses full-text and graph expansion; reach for this when you specifically want nearest-neighbour matches on meaning.
    ConnectorNo auth
  • Save a MEMORY about a SPECIFIC person — something YOU worked out on your own, unprompted, that the user never told you (a pattern you spotted, a fact you inferred from their calendar or email). If the user ASKED you to remember it, it's their note, not your memory — use add_note. @mention a name in `content` to link someone in your network. Read them back via get_person (relationship.memories). For a general fact not about one person, use memory_save instead.
    ConnectorNo auth