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627,079 tools. Updated 2026-10-01 12:44

"Information on Rag and Memory" matching MCP tools:

  • 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.
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  • 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.
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  • Download all records from a built dataset as text (Step 5 — final step). Returns the complete dataset content as a UTF-8 string directly in the response — no file download or separate URL needed. Call get_job_status after build_dataset and wait for status='completed' before calling this tool. Use the dataset_id from that completed response. Format guide: jsonl = LLM fine-tuning, rag = LangChain/LlamaIndex chunks, csv = spreadsheets, md = human-readable, xml = structured interchange. Binary formats (parquet, hf) cannot be returned via MCP — export them from the FlexOrch dashboard directly. Args: dataset_id: Dataset ID from the get_job_status completed build response. format: Text export format — jsonl, csv, json, md, xml, rag. Default: jsonl.
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  • Trigger semantic indexing for a dataset — required before using dataset.chunks (Pro+ plan). Starts an async indexing job that splits the dataset into RAG-ready text chunks, generates embeddings, and stores them for semantic search. Indexing is idempotent: calling it again on an already-indexed dataset re-indexes with fresh embeddings. Indexing typically completes in 10–60 seconds depending on dataset size. After indexing, use dataset.chunks(dataset_id) to retrieve the text chunks. Args: dataset_id: ID of the built dataset to index (from job.status after dataset.build).
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  • File catalog reads. view=files lists uploaded file metadata, optionally filtered by namespace, and checks ACL files_list. Returns {files}. view=supported_types returns kinds, extensions, mimeTypes, and extract notes for RAG uploads. That view checks no ACL and spends no quota (former files_types). Neither view writes, deletes, or sends email. Use index_document to upload. MCP indexing accepts UTF-8 text; REST multipart accepts PDF and Excel too.
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  • 🗑️ PERMANENTLY delete conversation thread(s) and their messages + user-facing state (tags, assignments, drafts, reminders, RAG chunks). Destructive and NOT undoable — requires confirm=true. Pass thread_id for one, or thread_ids for a bulk delete. Kept intentionally: call history (voice_sessions), usage/billing, traces, and outreach dedup are NOT removed. Note: for a live synced channel (Telegram/WhatsApp) this clears the LOCAL copy; a new inbound can re-create the thread on next sync. For livechat/voice/test/duel threads it's effectively permanent.
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    Destructive
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Matching MCP Servers

  • A
    license
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    quality
    B
    maintenance
    Serves UltraRAG memory to agents over stdio MCP, providing project-local and per-user global memory. It lets agents read and append standing memory and daily dialogue rounds in UltraRAG's format, with an optional browser view.
    4
    Apache 2.0
  • A
    license
    A
    quality
    B
    maintenance
    Enables persistent project memory for Hermes Agent by storing and retrieving wiki, code, and learning layers locally, with tools to recall, learn, retire, and ingest information beyond the context window.
    6
    MIT

Matching MCP Connectors

  • 🗑️ PERMANENTLY delete conversation thread(s) and their messages + user-facing state (tags, assignments, drafts, reminders, RAG chunks). Destructive and NOT undoable — requires confirm=true. Pass thread_id for one, or thread_ids for a bulk delete. Kept intentionally: call history (voice_sessions), usage/billing, traces, and outreach dedup are NOT removed. Note: for a live synced channel (Telegram/WhatsApp) this clears the LOCAL copy; a new inbound can re-create the thread on next sync. For livechat/voice/test/duel threads it's effectively permanent.
    Connector
    Destructive
    API key
  • 🗑️ PERMANENTLY delete conversation thread(s) and their messages + user-facing state (tags, assignments, drafts, reminders, RAG chunks). Destructive and NOT undoable — requires confirm=true. Pass thread_id for one, or thread_ids for a bulk delete. Kept intentionally: call history (voice_sessions), usage/billing, traces, and outreach dedup are NOT removed. Note: for a live synced channel (Telegram/WhatsApp) this clears the LOCAL copy; a new inbound can re-create the thread on next sync. For livechat/voice/test/duel threads it's effectively permanent.
    Connector
    Destructive
    API key
  • 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
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  • Curated working imports, snippets, and migration notes for one topic (agents, rag, wallet, payment, trustlines, …). Use when writing or migrating a fragment; unknown topics fall back to related doc chunks instead of failing. Prefer fetch_working_example for a complete runnable file, search_ai_framework_docs for open-ended lookup, and diagnose_framework_error for exceptions. Paid tools/call: $0.001 USDC or 1000 drops XRP; read-only catalog.
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  • 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.
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  • 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.
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  • Retrieve the full body of a licensed article using a buyer API token (opedd_buyer_live_* canonical; opedd_buyer_test_* for sandbox). Requires OPEDD_BUYER_TOKEN env var (create one at opedd.com/licenses after purchasing). Works for per-article Human republication licences (token scoped to that article) and licence orders: AI answers monthly and client display return full text; AI answers pay-per-request always returns a snippet (up to 300 words or 25% of the article, whatever delivery_mode is asked). Articles the publisher stopped licensing answer 403 ARTICLE_EXCLUDED. The publisher must have content delivery enabled and must have pushed content for the article. Phase 11 M2 RAG-extended shape: response includes 7 RAG-essential metadata fields — author, language, word_count, content_hash, image_urls, canonical_url, tags. On pre-2026-05-14 historical articles, optional fields (author/language/image_urls/canonical_url/tags) may be NULL. NULL means 'data unavailable for this article', NOT 'explicitly empty' — treat as data-missing when filtering; do not interpret as anti-match.
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  • Query the IA-QA methodology knowledge base. Returns structured testing guidelines, assertion strategies, thresholds, best practices, and relevant MCP tools for a given topic. Call without a topic to list all available topics. Topics: llm-unit-testing, rag-pipeline, prompt-stability, prompt-ab-testing, embedding-quality, eval-framework, semantic-testing, auto-testing, security, api-testing, ci-cd, multimodal, llm-data-security, agent-observability, pro-tips, learning-paths, golden-dataset, selector-drift, qa-recipes, playbooks. Not sure where to start testing an LLM, RAG pipeline or agent? Call without a topic (or with "start-here"): it maps what you are testing to the tools to call and the output field to gate CI on. A plain question such as "how do I test my RAG" also resolves to the right topic.
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  • Search PubMed (NCBI) for medical / life-sciences literature by keyword. Returns enriched article list: pmid, title, authors, journal, year, pub_types, plus a year-range + has-meta-analysis / has-review enrichment block. Ideal for medical RAG agents. Priced at $0.005 USDC on Base (x402). Pass a signed x402 v2 authorization as the '_payment' argument to unlock the paid response. Without it, the tool returns the 402 accept-list for your wallet to sign.
    ConnectorNo auth
  • Fetch one topic's RAG context (~200-500 tokens): source-verified claims (verbatim for Open-Access / public-domain sources, paraphrased derived summaries for copyrighted veterinary references) plus structured source citations (authority/title/url) and a `trust` block (raw trust axes + computed display_grade for this topic). Discover topic_ids with search_pet_topics first.
    ConnectorNo auth
  • Laurent Knauss' technical skills, grouped by domain (Agentic AI, RAG & Voice AI, Software engineering & Cloud, Automation & tooling). Each skill has a label and an optional short detail. Use this to assess fit for AI/agentic development roles.
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  • Fetch up to 10 public URLs and return each as clean Markdown, in one call — for research/RAG over several pages at once. Private/internal hosts are blocked.
    ConnectorNo auth
  • Store a long-term memory that persists across sessions and across every AI tool the user has connected to Mnemoverse (Claude, ChatGPT, Cursor, VS Code). Suited to durable information: a stated preference, a decision, a fact about people, roles or project setup, a lesson learned; transient chatter that only matters this turn does not belong here. Never store passwords, API keys, payment data, MFA codes, government IDs, or health records. Behavior: an importance gate may filter low-value writes, so the result tells you whether the memory was stored or filtered. Write `content` as a self-contained statement that still makes sense when recalled out of context.
    ConnectorOAuth