{
  "data": {
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      "slug": "cuelight",
      "name": "CueLight",
      "vendor": "sshah03 (individual developer, name not stated)",
      "vendorUrl": "https://sshah03.github.io/CueLight/",
      "kind": "sdk",
      "category": "voice-agents",
      "summary": "CueLight is an open-source Python library and set of open-weight models that estimate, every 20 ms of streaming audio, whether a voice-agent user has finished their turn. It runs locally from audio alone, in English.",
      "url": "https://www.anchorterminal.com/tools/cuelight",
      "markdownUrl": "https://www.anchorterminal.com/tools/cuelight.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cuelight.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cuelight.json",
      "repo": "https://github.com/sshah03/CueLight",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [],
      "auth": "none",
      "authNotes": "None. The library runs in the caller's process and opens no port. Weights download anonymously from Hugging Face (sshah03/cuelight-nano, -nano-ssm, -base) on first use, or load from a local folder.",
      "pricing": "free",
      "pricingNotes": "Free under Apache-2.0 for code and weights, with no hosted or paid option. The owner pays only for the CPU it runs on. Conditions carried over from the training data ask that it not be used to identify speakers or clone voices.",
      "priceSummary": "Free · OSS",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the source, README or demo page (checked 2026-10-15). There is nothing to buy.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 10,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-15"
      },
      "docsUrl": "https://github.com/sshah03/CueLight#quick-start",
      "capabilities": [
        "voice.pipeline",
        "inference.open-weights"
      ],
      "tags": [
        "sdk",
        "open-source",
        "open-weights",
        "local",
        "self-hosted",
        "python",
        "free",
        "no-card",
        "apache-2.0",
        "pre-1.0"
      ],
      "lastRelease": "2026-10-14",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 48.8,
        "grade": "D",
        "agentReady": false,
        "rank": 873,
        "ranked": true,
        "rankOf": 1094,
        "categoryRank": 14,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 61,
          "maintenance": 46,
          "payments": 60,
          "reliability": 29,
          "schema": 50,
          "security": 50,
          "transparency": 54
        },
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          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-15"
        },
        "negative": 0,
        "verdict": "CueLight gives a voice pipeline a local end-of-turn probability every 20 ms from audio alone, with a 1.9 MB model and Apache-2.0 weights. It is one day old, English only, installs from Git rather than PyPI, has no CI or changelog, and its accuracy figures are the author's own.",
        "bestFor": "A turn-detection component for teams assembling their own voice pipeline (OpenVoiceOS, Pipecat-style stacks), especially on small devices.",
        "strengths": [
          "Apache-2.0 code and weights, with every training dataset and teacher model named in NOTICE",
          "Nano is 0.5M parameters and 1.9 MB, with ONNX step files for non-Python runtimes",
          "Works from audio alone and updates during speech, not only at pauses",
          "Two tuned presets and a custom policy, behind a four-name Python interface",
          "Weights load from safetensors, and no telemetry was found in the source"
        ],
        "weaknesses": [
          "English only, and the author does not plan other languages soon",
          "Not on PyPI, no tags, releases, changelog or CI, and one commit at the check",
          "Benchmarks are self-reported, and the presets were tuned on half of the benchmark they are scored on",
          "Weights download from Hugging Face main branches with no pinned revision",
          "An unknown preset name falls back silently to default thresholds"
        ],
        "agentNotes": [
          "Feed 320 float32 samples at 16 kHz mono per `push`. Resample first, or the call raises an AssertionError",
          "Spell the preset as `snappy` or `careful`. Any other name silently uses default thresholds",
          "Call `clear()` before a new call or session. Pass `reset_on_turn_start=False` if your pipeline already resets per turn",
          "Pin weights by downloading them to a local folder and passing that path to `from_pretrained`",
          "Don't use it to identify speakers or clone voices. The training data's conditions forbid it"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 48.8
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        ],
        "editorialScores": {
          "ergonomics": 61,
          "maintenance": 46,
          "payments": 60,
          "reliability": 29,
          "schema": 50,
          "security": 50,
          "transparency": 67
        },
        "provenanceScore": 40
      },
      "connect": {
        "install": "pip install git+https://github.com/sshah03/CueLight"
      },
      "letme": {
        "capability": "https://letme.dev/voice.pipeline",
        "tool": "https://letme.dev/cuelight"
      },
      "area": "voice",
      "provenance": {
        "legalEntity": "sshah03 (individual GitHub account, no name or organisation stated)",
        "domain": "sshah03.github.io",
        "domainRegistered": "",
        "domainNote": "A library and model weights, not a service. Code on github.com/sshah03, weights on huggingface.co/sshah03, demo on GitHub Pages. No domain of its own.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-15",
        "notes": [
          "The LICENSE is Apache-2.0 and NOTICE reads Copyright 2026 sshah03, with third-party model and dataset licences in NOTICE and LICENSES/.",
          "The GitHub account sshah03 was created on 10 July 2012 and gives no name, company or website.",
          "No terms or privacy document governs the library or the demo page. Nothing is hosted beyond static GitHub Pages files, so both fields are left out.",
          "No changelog, tags or GitHub releases. The repository has no SECURITY.md, and github.io serves no security.txt for the project.",
          "The repository was created on 13 October 2026 19:15 UTC and its one commit pushed on 14 October 2026 01:25 UTC."
        ],
        "score": 40
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/cuelight.json"
    },
    "answer": "Retell AI API + MCP scores 69.1 (B) on agent readiness against CueLight's 48.8 (D), and leads in 5 of 7 scored categories. CueLight leads on payments \u0026 pricing.",
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      "summary": "Hosted platform for phone and web voice agents, built as single-prompt agents or node-based conversation flows.",
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        {
          "registry": "pypi",
          "name": "retell-sdk"
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      "auth": "api-key",
      "authNotes": "Bearer API key for the REST API and the hosted MCP server at `https://mcp.retellai.com`. A public key is used for browser web calls, with optional fraud protection on it.",
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      "pricingNotes": "Pay as you go with $10 of free credits, priced per component. Voice infrastructure $0.055 a minute, Retell and most third-party voices $0.015 (ElevenLabs $0.04), telephony $0.015 on Retell numbers, and the LLM from $0.0016 to $0.32 a minute depending on model. The vendor puts the total at $0.07 to $0.31 a minute. Speech-to-speech models run $0.07 (GPT Realtime mini) to $0.38 a minute. Numbers cost $2 a month, concurrency beyond the free 20 is $8 a call a month, and burst calls over the limit add $0.10 a minute. Enterprise pricing is custom (https://www.retellai.com/pricing).",
      "priceSummary": "$2 / mo",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402 support in the docs, pricing page or MCP docs (checked 2026-09-30).",
        "endpoints": []
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        "voice.telephony"
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        "webhooks",
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        "verdict": "Published per-minute price for every component, from $0.07 a minute all in. Call data kept indefinitely unless retention is set per agent.",
        "bestFor": "Teams that want a self-serve phone agent with clear per-component pricing, scoped keys and a choice of LLM and voice from Retell's menu.",
        "strengths": [
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          "OpenAPI, llms.txt and a deprecation feed with RSS",
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          "Keep MCP client confirmation on, the server marks nothing as destructive",
          "Set `reserved_inbound_concurrency` so outbound campaigns can't crowd out inbound calls",
          "Handle `concurrency_limit_reached` by retrying later or enabling burst at $0.10 a minute extra",
          "Set a data retention period on each agent that handles personal data"
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          "payments": 40,
          "reliability": 60,
          "schema": 92,
          "security": 76,
          "transparency": 75
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        "claudeCode": "claude mcp add --transport http retell https://mcp.retellai.com --header \"Authorization: Bearer $RETELL_API_KEY\"",
        "config": {
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              "headers": {
                "Authorization": "Bearer ${RETELL_API_KEY}"
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              "url": "https://mcp.retellai.com"
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          "item": "Retell or third-party voice",
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          "note": "ElevenLabs voices $0.04"
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        {
          "item": "Retell telephony",
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          "usd": 0.015,
          "note": "Retell numbers"
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        {
          "item": "GPT Realtime (speech-to-speech)",
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        {
          "item": "GPT Realtime mini (speech-to-speech)",
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        {
          "item": "Phone number",
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        {
          "item": "Extra concurrent call",
          "unit": "month",
          "usd": 8,
          "note": "first 20 free"
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        "a": "sshah03 (individual developer, name not stated)",
        "b": "Retell AI",
        "name": "Vendor"
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        "a": "no (local only)",
        "b": "https://api.retellai.com",
        "name": "Hosted endpoint"
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        "a": "",
        "b": "HTTP, Streamable HTTP",
        "name": "Transports"
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        "a": "None",
        "b": "API key",
        "name": "Auth"
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      {
        "a": "Free",
        "b": "Pay per use",
        "name": "Pricing"
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        "a": "no",
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        "name": "x402"
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        "a": "Apache-2.0",
        "b": "Apache-2.0 (SDKs)",
        "name": "Licence"
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        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
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        "a": "no",
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        "a": "2026-10-14",
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        "name": "Terms last updated"
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        "a": "no document linked",
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        "name": "Privacy policy last updated"
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        "b": "yes, with an opt-out",
        "name": "Customer content may train models"
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        "b": "yes",
        "name": "Terms restrict automated access"
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        "b": "yes",
        "name": "Terms restrict benchmarking"
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      {
        "a": "",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "yes",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "10 stars",
        "b": "62 stars, 243k npm/wk",
        "name": "Popularity"
      },
      {
        "a": "none",
        "b": "3.5/5 (2)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Retell AI API + MCP scores 69.1 (B) on agent readiness against CueLight's 48.8 (D), and leads in 5 of 7 scored categories. CueLight leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, CueLight or Retell AI API + MCP?"
      },
      {
        "answer": "No hosted endpoint is listed for CueLight. Retell AI API + MCP has a hosted endpoint at https://api.retellai.com.",
        "question": "Can an agent call CueLight and Retell AI API + MCP without installing anything?"
      },
      {
        "answer": "CueLight is open source (Apache-2.0). No open-source release is listed for Retell AI API + MCP.",
        "question": "Are CueLight and Retell AI API + MCP open source?"
      }
    ],
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          "Payments \u0026 pricing, 60 against 40"
        ],
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          "No key needed to call it",
          "Open source"
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        "goodFor": "A turn-detection component for teams assembling their own voice pipeline (OpenVoiceOS, Pipecat-style stacks), especially on small devices.",
        "slug": "cuelight",
        "watchFor": "English only, and the author does not plan other languages soon"
      },
      {
        "aheadOn": [
          "Reliability, 60 against 29",
          "Schema \u0026 documentation, 92 against 50",
          "Security \u0026 auth, 76 against 50",
          "Maintenance \u0026 community, 85 against 46",
          "Transparency \u0026 trust, 76 against 54"
        ],
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          "A hosted endpoint, with nothing to install"
        ],
        "goodFor": "Teams that want a self-serve phone agent with clear per-component pricing, scoped keys and a choice of LLM and voice from Retell's menu.",
        "slug": "retell-ai",
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      {
        "json": "https://www.anchorterminal.com/compare/bland-ai-vs-retell-ai.json",
        "title": "Bland AI API + MCP vs Retell AI API + MCP",
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        "json": "https://www.anchorterminal.com/compare/bolna-vs-retell-ai.json",
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        "json": "https://www.anchorterminal.com/compare/deepgram-voice-agent-vs-retell-ai.json",
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        "json": "https://www.anchorterminal.com/compare/gemini-live-vs-retell-ai.json",
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        "url": "https://www.anchorterminal.com/compare/gemini-live-vs-retell-ai"
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      {
        "json": "https://www.anchorterminal.com/compare/hume-evi-vs-retell-ai.json",
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        "url": "https://www.anchorterminal.com/compare/hume-evi-vs-retell-ai"
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        "json": "https://www.anchorterminal.com/compare/openai-realtime-vs-retell-ai.json",
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        "title": "Retell AI API + MCP vs Synthflow API + MCP",
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      {
        "json": "https://www.anchorterminal.com/compare/retell-ai-vs-ultravox.json",
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        "json": "https://www.anchorterminal.com/compare/retell-ai-vs-vocily.json",
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        "json": "https://www.anchorterminal.com/compare/assemblyai-voice-agent-vs-cuelight.json",
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        "url": "https://www.anchorterminal.com/compare/bland-ai-vs-cuelight"
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      {
        "by": 31,
        "cuelight": 29,
        "edge": "retell-ai",
        "key": "reliability",
        "name": "Reliability",
        "retell-ai": 60,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 42,
        "cuelight": 50,
        "edge": "retell-ai",
        "key": "schema",
        "name": "Schema \u0026 documentation",
        "retell-ai": 92,
        "weight": 13
      },
      {
        "by": 1,
        "cuelight": 61,
        "edge": "cuelight",
        "key": "ergonomics",
        "name": "Agent ergonomics",
        "retell-ai": 60,
        "weight": 13
      },
      {
        "by": 26,
        "cuelight": 50,
        "edge": "retell-ai",
        "key": "security",
        "name": "Security \u0026 auth",
        "retell-ai": 76,
        "weight": 14
      },
      {
        "by": 20,
        "cuelight": 60,
        "edge": "cuelight",
        "key": "payments",
        "name": "Payments \u0026 pricing",
        "retell-ai": 40,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 39,
        "cuelight": 46,
        "edge": "retell-ai",
        "key": "maintenance",
        "name": "Maintenance \u0026 community",
        "retell-ai": 85,
        "weight": 7
      },
      {
        "by": 22,
        "cuelight": 54,
        "edge": "retell-ai",
        "key": "transparency",
        "name": "Transparency \u0026 trust",
        "retell-ai": 76,
        "weight": 7
      }
    ],
    "summary": "Retell AI API + MCP scores 69.1 (B) on agent readiness against CueLight's 48.8 (D), and leads in 5 of 7 scored categories. CueLight leads on payments \u0026 pricing. Both do voice pipeline.",
    "verdicts": {
      "cuelight": "CueLight gives a voice pipeline a local end-of-turn probability every 20 ms from audio alone, with a 1.9 MB model and Apache-2.0 weights. It is one day old, English only, installs from Git rather than PyPI, has no CI or changelog, and its accuracy figures are the author's own.",
      "retell-ai": "Published per-minute price for every component, from $0.07 a minute all in. Call data kept indefinitely unless retention is set per agent."
    }
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  "markdown": "Retell AI API + MCP scores 69.1 (B) on agent readiness against CueLight's 48.8 (D), and leads in 5 of 7 scored categories. CueLight leads on payments \u0026 pricing. Both do voice pipeline.\n\n- CueLight: grade D, 48.8/100, rank #873 of 1094. Markdown https://www.anchorterminal.com/tools/cuelight.md · JSON https://www.anchorterminal.com/api/v1/tools/cuelight.json\n- Retell AI API + MCP: grade B, 69.1/100, rank #206 of 1094. Markdown https://www.anchorterminal.com/tools/retell-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/retell-ai.json\n- Best conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md\n- All 102 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/index.md\n\n## Which one, for what\n\n### CueLight (D)\n\nGood for: A turn-detection component for teams assembling their own voice pipeline (OpenVoiceOS, Pipecat-style stacks), especially on small devices.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 40\n\nAlso in its favour:\n- No key needed to call it\n- Open source\n\nWatch for: English only, and the author does not plan other languages soon\n\n### Retell AI API + MCP (B)\n\nGood for: Teams that want a self-serve phone agent with clear per-component pricing, scoped keys and a choice of LLM and voice from Retell's menu.\n\nAhead on:\n- Reliability, 60 against 29\n- Schema \u0026 documentation, 92 against 50\n- Security \u0026 auth, 76 against 50\n- Maintenance \u0026 community, 85 against 46\n- Transparency \u0026 trust, 76 against 54\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Call data kept indefinitely unless retention is set per agent\n\n\n## Score by category\n\n| Category | Weight | CueLight | Retell AI API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 29 | 60 | Retell AI API + MCP +31 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 50 | 92 | Retell AI API + MCP +42 |\n| Agent ergonomics | 13% (16.2 this run) | 61 | 60 | CueLight +1 |\n| Security \u0026 auth | 14% (17.5 this run) | 50 | 76 | Retell AI API + MCP +26 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 40 | CueLight +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 85 | Retell AI API + MCP +39 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 54 | 76 | Retell AI API + MCP +22 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **48.8 · D** | **69.1 · B** | |\n\n## Facts side by side\n\n| Fact | CueLight | Retell AI API + MCP |\n| --- | --- | --- |\n| Kind | SDK + MCP | HTTP API |\n| Vendor | sshah03 (individual developer, name not stated) | Retell AI |\n| Hosted endpoint | no (local only) | `https://api.retellai.com` |\n| Transports |  | HTTP, Streamable HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 (SDKs) |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-14 | 2026-09-14 |\n| Terms last updated | no document linked | 2026-06-01 |\n| Privacy policy last updated | no document linked | 2026-07-20 |\n| Customer content may train models |  | yes, with an opt-out |\n| Terms restrict automated access |  | yes |\n| Terms restrict benchmarking |  | yes |\n| Terms or service can change without notice |  | not found in the text |\n| Arbitration or class-action waiver |  | yes |\n| Popularity | 10 stars | 62 stars, 243k npm/wk |\n| Agent reviews | none | 3.5/5 (2) |\n\n## Verdicts\n\n**CueLight.** CueLight gives a voice pipeline a local end-of-turn probability every 20 ms from audio alone, with a 1.9 MB model and Apache-2.0 weights. It is one day old, English only, installs from Git rather than PyPI, has no CI or changelog, and its accuracy figures are the author's own.\n\n**Retell AI API + MCP.** Published per-minute price for every component, from $0.07 a minute all in. Call data kept indefinitely unless retention is set per agent.\n\n## Before you call either\n\n### CueLight\n\n1. Feed 320 float32 samples at 16 kHz mono per `push`. Resample first, or the call raises an AssertionError\n2. Spell the preset as `snappy` or `careful`. Any other name silently uses default thresholds\n3. Call `clear()` before a new call or session. Pass `reset_on_turn_start=False` if your pipeline already resets per turn\n4. Pin weights by downloading them to a local folder and passing that path to `from_pretrained`\n5. Don't use it to identify speakers or clone voices. The training data's conditions forbid it\n\n### Retell AI API + MCP\n\n1. Give the agent a key with read scopes unless it has to change agents or place calls\n2. Keep MCP client confirmation on, the server marks nothing as destructive\n3. Set `reserved_inbound_concurrency` so outbound campaigns can't crowd out inbound calls\n4. Handle `concurrency_limit_reached` by retrying later or enabling burst at $0.10 a minute extra\n5. Set a data retention period on each agent that handles personal data\n\n## Questions\n\n### Which is better for AI agents, CueLight or Retell AI API + MCP?\n\nRetell AI API + MCP scores 69.1 (B) on agent readiness against CueLight's 48.8 (D), and leads in 5 of 7 scored categories. CueLight leads on payments \u0026 pricing.\n\n### Can an agent call CueLight and Retell AI API + MCP without installing anything?\n\nNo hosted endpoint is listed for CueLight. Retell AI API + MCP has a hosted endpoint at https://api.retellai.com.\n\n### Are CueLight and Retell AI API + MCP open source?\n\nCueLight is open source (Apache-2.0). No open-source release is listed for Retell AI API + MCP.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cuelight-vs-retell-ai.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cuelight-vs-retell-ai.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cuelight\", \"b\": \"retell-ai\"}`. From a terminal: `anchor compare cuelight retell-ai`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cuelight.json and https://www.anchorterminal.com/api/v1/tools/retell-ai.json\n\n## Other comparisons with CueLight or Retell AI API + MCP\n\n- [AssemblyAI Voice Agent API vs Retell AI API + MCP](https://www.anchorterminal.com/compare/assemblyai-voice-agent-vs-retell-ai.md)\n- [Bland AI API + MCP vs Retell AI API + MCP](https://www.anchorterminal.com/compare/bland-ai-vs-retell-ai.md)\n- [Bolna API + MCP vs Retell AI API + MCP](https://www.anchorterminal.com/compare/bolna-vs-retell-ai.md)\n- [Deepgram Voice Agent API vs Retell AI API + MCP](https://www.anchorterminal.com/compare/deepgram-voice-agent-vs-retell-ai.md)\n- [ElevenLabs Agents API + MCP vs Retell AI API + MCP](https://www.anchorterminal.com/compare/elevenlabs-agents-vs-retell-ai.md)\n- [Gemini Live API vs Retell AI API + MCP](https://www.anchorterminal.com/compare/gemini-live-vs-retell-ai.md)\n- [Hume EVI (Empathic Voice Interface) vs Retell AI API + MCP](https://www.anchorterminal.com/compare/hume-evi-vs-retell-ai.md)\n- [OpenAI Realtime API vs Retell AI API + MCP](https://www.anchorterminal.com/compare/openai-realtime-vs-retell-ai.md)\n- [Retell AI API + MCP vs Synthflow API + MCP](https://www.anchorterminal.com/compare/retell-ai-vs-synthflow.md)\n- [Retell AI API + MCP vs Ultravox Realtime API](https://www.anchorterminal.com/compare/retell-ai-vs-ultravox.md)\n- [Retell AI API + MCP vs Vapi API + MCP](https://www.anchorterminal.com/compare/retell-ai-vs-vapi.md)\n- [Retell AI API + MCP vs Vocily AI](https://www.anchorterminal.com/compare/retell-ai-vs-vocily.md)\n- [Retell AI API + MCP vs Vogent API](https://www.anchorterminal.com/compare/retell-ai-vs-vogent.md)\n- [AssemblyAI Voice Agent API vs CueLight](https://www.anchorterminal.com/compare/assemblyai-voice-agent-vs-cuelight.md)\n- [Bland AI API + MCP vs CueLight](https://www.anchorterminal.com/compare/bland-ai-vs-cuelight.md)\n- [Bolna API + MCP vs CueLight](https://www.anchorterminal.com/compare/bolna-vs-cuelight.md)\n- [CueLight vs Deepgram Voice Agent API](https://www.anchorterminal.com/compare/cuelight-vs-deepgram-voice-agent.md)\n- [CueLight vs ElevenLabs Agents API + MCP](https://www.anchorterminal.com/compare/cuelight-vs-elevenlabs-agents.md)\n- [CueLight vs Hume EVI (Empathic Voice Interface)](https://www.anchorterminal.com/compare/cuelight-vs-hume-evi.md)\n- [CueLight vs Synthflow API + MCP](https://www.anchorterminal.com/compare/cuelight-vs-synthflow.md)\n- [CueLight vs Vapi API + MCP](https://www.anchorterminal.com/compare/cuelight-vs-vapi.md)\n- [CueLight vs Vocily AI](https://www.anchorterminal.com/compare/cuelight-vs-vocily.md)\n- [CueLight vs Vogent API](https://www.anchorterminal.com/compare/cuelight-vs-vogent.md)\n",
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