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133,525 tools. Last updated 2026-05-25 17:48

"Chat with RAG (Retrieval-Augmented Generation)" matching MCP tools:

  • Schedule a downgrade to Free at the end of the current billing period. The org keeps its current plan (Pro or Scale) and paid limits until the period ends. No-op when already on Free. Consent-gated. Two consent surfaces, you pick via `mode`: (1) `chat` (default): FIRST call returns { status: 'confirmation_required', confirm_token, message, expires_in }; surface to your user and re-call within 60s with `confirm_token` set. (2) `web`: FIRST call returns { status: 'approval_required', approval_url, polling_url }; print approval_url in chat, user clicks + approves, then poll polling_url for the result.
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  • Check the status and generation progress of a site. Returns detailed progress information including: - stage: Current step (initialization, validation, research, strategy, generation, assembly, completion) - overallProgress: Total progress 0-100 across all stages (use this for progress bars) - stageProgress: Progress within current stage 0-100 - message: Human-readable status message - isComplete: Boolean - stop polling when true Use the versionId returned from create_site for real-time progress polling. Poll every 5-10 seconds while isComplete is false.
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  • Search the company's connected knowledge across every source — Drive, SharePoint, Confluence, Slack, Notion — with cited synthesized answers, lifecycle awareness, and refusal-on-weak-context. Returns a written answer with [n] citations plus the ranked source chunks. Modes: `fast` (1,500 kT — retrieval-only, no synthesis), `standard` (12,500 kT — default; synthesized answer over the top retrieval set), `deep` (25,000 kT — wider retrieval + premium synthesis for complex questions). Pick the cheapest tier that answers the question. Responses are capped at 25,000 output tokens per Claude Connectors policy; if truncated, structured metadata carries `truncated: true` and `query_id` so the agent can call `get_source_detail` for full provenance.
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  • [cost: rag (one embed + one vector search) | read-only, network: outbound to embed model only | rate-limited per IP] Like `lookup_response_code` but augmented: returns the static RFC entry PLUS the top vendor-specific RAG hits for the exact code (and any free-text context the user pasted). When the static entry carries known vendor-specific reason-phrase variants (e.g. 484 + opensips → 'Invalid FROM' from `parse_from.c`), those phrases are folded into the embed query so the right vendor docs surface. Use when the user asks 'why did <vendor> reject this with <code>?' and you want vendor-grounded common causes, not just the RFC text. Especially helpful for fax-rejection paths - 488 / 415 / 606 on a T.38 reinvite (`m=image udptl t38`) is one of the most common 488 variants and the tool surfaces FreeSWITCH `mod_spandsp` / Cisco CUBE / AudioCodes T.38 docs alongside the RFC text. Pair with: `lookup_response_code` first (cheaper); `lint_sip_request` when the code is 4xx and they have the offending request; `compare_sdp_offer_answer` for 488/415 caused by a T.38 reinvite SDP mismatch; `validate_stir_shaken_identity` when the code is 438; `stir_attestation_explainer` for STIR-shaped codes (428/436/437/438/608); `dns_diagnose_sip_target` when the code is 503 / 408 and routing is suspect.
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  • Find working SOURCE CODE examples from 37 indexed Senzing GitHub repositories. REQUIRED: either `query` (string, for search) or `repo` with `file_path` or `list_files=true` — the call WILL FAIL without one. Three modes: (1) Search: pass `query` to find examples across all repos, (2) File listing: pass `repo` + `list_files=true`, (3) File retrieval: pass `repo` + `file_path`. Indexes source code (.py, .java, .cs, .rs) and READMEs — NOT build/data files. For sample data, use get_sample_data. Covers Python, Java, C#, Rust SDK patterns: initialization, ingestion, search, redo, configuration, message queues, REST APIs. Use max_lines to limit large files. Returns GitHub raw URLs for file retrieval.
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  • [cost: free (pure CPU, no network) | read-only] Instant static lookup of a SIP response code (100-699). Returns name, RFC anchor, category, description, common operator-flavored causes, and known vendor-specific reason-phrase variants (e.g. OpenSIPS emits 484 'Invalid FROM' on From-header parse failure). USE FIRST when the user pastes or asks about any 3-digit SIP code - sub-millisecond, no API cost. Pair with: `troubleshoot_response_code` for vendor-specific RAG hits beyond the static entry; `lint_sip_request` when the code is 4xx and the user has the offending request; `stir_attestation_explainer` for STIR-shaped codes (428/436/437/438/608); `validate_stir_shaken_identity` when the code is 438 and they have the JWS.
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Matching MCP Servers

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    Enhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.
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    MIT
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    Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.
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    MIT

Matching MCP Connectors

  • Conversational access to advertising performance data, creative analysis, and campaign insights

  • Search, order, and manage eSIM data packages for 190+ countries.

  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.
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  • Get the list of legal document templates available for generation on the platform (e.g. NDA, employment agreement, stock purchase agreement). For corporate services like 83(b) filing or registered agent, use get_available_corporate_services instead.
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  • Deep intelligence on a TikTok creator by handle. Returns viral DNA scores (viral_dna_score, replicability_score, originality_score, consistency_score, audience_fatigue), format fingerprint, top 5 videos with transcripts, content gaps, AND a `recommended_chain` field with pre-filled next tool calls. USE WHEN the user references a creator by @handle, asks "analyze X", wants competitor research, or needs creator context before generating content. The recommended_chain suggests which tools to call next (match_voice, trend_pulse, viral_remix) with parameters pre-filled — review and execute them as appropriate. TikTok only in v1. Costs 5 credits. 1-hour cache per handle. TOOL HEALTH: Every response includes a `quality` field with a level (full | partial | degraded) and a reason. If quality.level is partial or degraded, you MUST flag this to the user explicitly in chat (e.g. "Heads up — this call returned partial data: <reason>") before reporting any results. Never silently route around a degraded response. REPORTING: When you summarize this in chat, you MUST surface viral_dna.viral_dna_signals, viral_dna.replicability_signals, viral_dna.originality_signals (each as bullet lists with the cited evidence string verbatim) AND viral_dna.would_fail_because verbatim AND provenance.video_post_dates so the user can see freshness. Never hide the evidence array behind a paraphrase — these are the auditability layer.
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  • Search historical voice calls in this workspace by participant name, contact_id, thread, channel, source, and/or date range. Returns one row per call (NOT per turn) with call_id, duration_seconds, outcome, direction, started_at, source, channel_label, and parent_thread_id (the originating chat thread for Telegram-group / Twilio-outbound / Meet calls). Pair with calls.get_transcript(call_id) for the full per-turn transcript. Use this instead of messages.read_history for cross-thread call queries — group calls and Meet sessions live on per-call sub-threads, not on the parent chat thread.
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  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
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  • End-to-end deploy: generate strategy → train → deploy live. One of `prompt` (free-form NL), `preset` (curated winning strategy), or `community_id` (copy a published community strategy) is required. If more than one is passed, precedence is community_id > preset > prompt. Args: prompt: Natural-language strategy description (e.g. "Buy when RSI < 30, sell > 70"). symbol: Currency pair to backtest on. One of: EURUSD, USDJPY, GBPUSD, USDCHF, USDCAD, AUDUSD, NZDUSD. Default EURUSD. timeframe: Candle granularity. One of: 1min, 5min, 15min, 1h. Default 15min. claude_model: Which Claude variant to use for code generation. "sonnet" (default — best quality, 1/day free) or "haiku" (faster, 3/day free). Ignored when `preset` is set (no generation needed). preset: Curated winning-strategy slug. Skips Claude generation entirely — deploys a pre-saved strategy known to backtest well on the chosen symbol. Available slugs: ema_cross_fast, momentum, scalper_stack, sma_only, trend_ema, volatility, bb_squeeze, all_mix, pivot_kid_ema. Not every slug exists for every symbol — call list_models afterwards to confirm what deployed. community_id: Copy-trade a published community strategy. Pass the `id` of an entry from `browse_community`. Loads that exact strategy code, skips Claude generation, then trains + deploys it. `symbol`/`timeframe` still apply to the backtest+deploy. webhook_url: Optional webhook to receive live signals. telegram_chat_id: Optional Telegram chat ID for signal delivery. Returns IMMEDIATELY (the deploy runs in the background so the live card can stream progress) with: - job_token (str): pass to get_deploy_result to fetch the final result. - poll_url (str): the card polls this for live progress; you can ignore it. - pending (bool): always true here — the deploy is still running. - symbol, timeframe (str). Call this EXACTLY ONCE per request. Pass the user's words as `prompt`; do not pre-pick presets/community strategies — the server routes (vague → a proven community strategy, specific rules → a fresh generation). NEXT STEP (always): call get_deploy_result(job_token) ONCE — it blocks until the deploy finishes and returns the out-of-sample stats + `stem` + `source`/`author` as TEXT so you can summarize. The live card already shows the chart, so you do NOT need get_model_chart. If source='community', tell the user it used a pre-existing strategy by @author and offer to generate a custom one.
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  • Returns runnable code that creates a Solana keypair. Solentic cannot generate the keypair for you and never sees the private key — generation must happen wherever you run code (the agent process, a code-interpreter tool, a Python/Node sandbox, the user's shell). The response includes the snippet ready to execute. After running it, fund the resulting publicKey and call the `stake` tool with {walletAddress, secretKey, amountSol} to stake in one call.
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use workspace.search for that.
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  • AI RAG chat, document analysis, shareable summaries on workspaces and shares. Call action='describe' for the full action/param reference. Destructive: chat-delete. Side effects: chat-create/message-send consume credits; chat-cancel terminates an in-progress message (partial tokens billed; idempotent). Verbosity (detail param): chat-list/message-list default to terse (compact rows). chat-details/message-details default to full (drill-down). Pass an explicit detail='standard'|'full' to override.
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  • Start async generation of a research report (15 credits). IMPORTANT: Call atlas_list_report_types first to get valid report_type values and required inputs. Returns report_id and task_id. Poll with careerproof_task_status(task_id) or atlas_get_report(report_id) until status='completed', then download PDF with atlas_download_report(report_id).
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  • Share management: create/update/delete, archive, password auth, members, quickshare, AI instructions. Call action='describe' for the full action/param reference. Destructive: delete (permanent). ⚠️ intelligence on create COSTS CREDITS (10/page) — default false unless user explicitly requests RAG. Verbosity (detail param): list/available/members default to terse (compact rows). public-details defaults to standard. details defaults to full (drill-down). Pass an explicit detail='terse'|'standard'|'full' to override.
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  • Enable or disable an AI module on a site. The module must be in the plan's available module list. Requires: API key with write scope. Args: slug: Site identifier module_name: Module to toggle. Available modules: "chatbot" (AI chat widget), "seo" (SEO optimization), "translation" (content translation), "content" (AI content generation) Returns: {"module": "chatbot", "enabled": true, "message": "Module enabled"} Errors: NOT_FOUND: Unknown slug or module not in plan VALIDATION_ERROR: Invalid module name
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  • RFC 8414 / RFC 9728 OAuth Authorization Server / Protected Resource Metadata. Returns the same metadata document the AS publishes at `GET /.well-known/openid-configuration`, augmented with AAP-specific extensions (authorization_details_types_supported, aap_claims_supported, dpop_signing_alg_values_supported).
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