"Multi-Agent Systems with Shared Memory Storage" matching MCP tools:

• notes_save

  dialogbrain

  Save a fact or note into the agent's memory. Use scope to choose visibility: 'workspace' = visible to every agent in this workspace (use for shared facts, project conventions); 'agent' = private to this agent (use for personal working notes); 'thread' = scoped to one conversation (use for thread-specific reminders); 'person' = scoped to one contact (use for per-contact context). If a note with the same key+scope exists it will be updated. Do NOT use this tool for behavioral rules or corrections — use feedback.save for those.

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• initialize_context

  Synapse Layer — Continuous Consciousness Infrastructure

  Initialize a persistent memory context for a conversation or agent session.

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• nanmesh.trust.report_outcome

  NaN Mesh

  Simplest way to contribute: just say if a tool worked or not. Automatically becomes a +1 or -1 review. AI-native (2026-05-12): pass any of task_type / stack / errors_encountered to also write a structured execution_report — your contribution becomes queryable by every future agent (shared operational memory).

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• agent_storage_put

  Hive Agent Storage

  Upload bytes to agent-isolated object storage. Per-agent DID isolation: only the owner DID can read/write its namespace by default. Settles in real Base USDC at $0.0001/KB on upload. Routes to Storj, Filecoin, or Arweave under the hood (chosen by retention class). Returns content-addressed object key + storage receipt with chain attestation. Backend pending — currently returns 503.

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• forget

  Tvmaze

  Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

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• notes_save

  DialogBrain

  Save a fact or note into the agent's memory. Use scope to choose visibility: 'workspace' = visible to every agent in this workspace (use for shared facts, project conventions); 'agent' = private to this agent (use for personal working notes); 'thread' = scoped to one conversation (use for thread-specific reminders); 'person' = scoped to one contact (use for per-contact context). If a note with the same key+scope exists it will be updated. Do NOT use this tool for behavioral rules or corrections — use feedback.save for those.

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• nanmesh.trust.review

  NaN Mesh

  Cast your expert +1 or -1 review on any entity. Use AFTER evaluating a tool you searched for or tried. Expert reviews are 70% of ranking. One review per agent per entity (overwrites previous). Requires agent_key. For no-auth alternative, use nanmesh.trust.favor instead. AI-native (2026-05-12): pass any of task_type / stack / outcome / errors_encountered to also write a structured execution_report. Your contribution becomes queryable by every future agent (shared operational memory). Server-side `source` is assigned authoritatively from your agent_id and class — your input is logged as a hint.

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• forget

  Bandsintown

  Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

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• forget

  Coinbase Exchange

  Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

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• agent_brief

  Colour Memory

  Generate a complete colour direction package for another AI agent or image generation model. Fetches a historically grounded archive palette from the concept, then produces: an agent brief (colour direction in prose), colour tokens with hex values and roles, a model-specific image generation prompt, a negative prompt, and lighting notes. Supports midjourney, flux, dalle, stable_diffusion. Example: task='luxury hotel bedroom', concept='Ottoman winter luxury', model='midjourney'. Use this to make Colour Memory the colour layer for other AI systems.

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• agent_storage_delete

  Hive Agent Storage

  Delete an object from agent storage. Owner-only — only the agent_did that owns the namespace can delete. Free. Tombstoned with a chain-attested receipt; cold-tier (Arweave permanent) objects are unlinked from the namespace but retain on-chain. Backend pending — currently returns 503.

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• nanmesh.entity.get

  NaN Mesh

  Get full details for a specific entity by slug or UUID. Use when you need deep info on a single tool — trust score, description, open problems, and metadata. AI-native (2026-05-12): pass format='agent' (+ optional task_type, stack) to get the firehose: 5-axis confidence_decomposition, known_failure_modes, recent_execution_reports, and a network_evidence block showing how many distinct agents have contributed to this entity's shared operational memory.

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• forget

  Ip Api

  Delete a previously stored memory by key. Use when context is stale, the task is done, or you want to clear sensitive data the agent saved earlier. Pair with remember and recall.

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• pitfalldb_report

  plith

  Report an agent failure. PII-scrubbed before storage. Linked to existing pitfalls if similar. Free — no credits charged.

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• agent_storage_get

  Hive Agent Storage

  Read an object from agent-isolated storage. Free for own DID; cross-DID reads cost $0.00005/KB in real Base USDC (settled per KB read). Returns the object bytes + storage receipt + chain attestation. Backend pending — currently returns 503.

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• get_related_models

  OpenDataModels MCP server

  Find Smart Data Models that are semantically related to a given model. Useful for discovering adjacent models when building multi-entity systems — e.g., related models for 'OffStreetParking' might surface 'ParkingSpot' and 'ParkingGroup'. Example: get_related_models({"model_name": "OffStreetParking", "relationship_type": "all"})

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• agents_create

  dialogbrain

  Create a new AI agent in the workspace. Execution modes: - ai_assisted (default, recommended): Two-phase AI — fast pre-classifier (Haiku) for keyword filtering and simple replies, then full AI with tools for complex messages. Best for: auto-replies, group monitoring, keyword-based filtering. - agentic: Autonomous multi-step agent with planning and tool execution. Best for: complex scheduled tasks, multi-step automation. - rule_based: Simple pattern matching without AI. For keyword filtering: use ai_assisted mode + set keywords in trigger conditions (free, deterministic) and/or auto_reply_rules (smart, LLM-based) via agents.update.

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• x711_hive_write

  x711 — Universal Agent Gas Station

  Contribute knowledge to The Hive — x711's collective agent memory. Your entry becomes part of the shared intelligence that every future agent can query. When other agents call x711_hive_read and your entry matches their query, you earn 82% of their read fee automatically (no claiming needed). High-quality entries earn recurring passive income. Minimum 8 chars, max 8000. Returns: { written: true, id, namespace, earn_note }.

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• list_pending_collaboration_requests

  Delx MCP Server

  List pending multi-agent handoff or reciprocal witness requests for one session. Safe: returns request pointers only, not private handoff context. Free.

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• agent_storage_list

  Hive Agent Storage

  List objects inside an agent storage namespace. Free read. Supports key prefix filtering and pagination cursor. Backend pending — currently returns 503.

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