# Giggy Speech to Text vs Mistral Voxtral Transcribe

> Mistral Voxtral Transcribe scores 63.1 (B) to Giggy Speech to Text's 54.5 (C) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe
- Markdown: https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe.md (~6,100 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-04

Mistral Voxtral Transcribe scores 63.1 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category. Both do speech-to-text.

- Giggy Speech to Text: grade C, 54.5/100, rank #805 of 1349. Markdown https://www.anchorterminal.com/tools/giggy-stt.md · JSON https://www.anchorterminal.com/api/v1/tools/giggy-stt.json
- Mistral Voxtral Transcribe: grade B, 63.1/100, rank #475 of 1349. Markdown https://www.anchorterminal.com/tools/mistral-voxtral-transcribe.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-voxtral-transcribe.json
- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md
- All 253 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md

## Which one, for what

### Giggy Speech to Text (C)

Good for: Agents and voice pipelines that need plain transcripts of recorded or live speech at a few cents an hour, or free for clips under 25 minutes, and can convert audio to 16 kHz mono WAV first.

Also in its favour:
- No incidents deducted, where Mistral Voxtral Transcribe loses 6 points for them

Watch for: Recorded input must be PCM16 mono 16 kHz WAV, so MP3, M4A, stereo or other sample rates need converting before upload

### Mistral Voxtral Transcribe (B)

Good for: Suited to low-cost batch transcription with diarisation in the 13 supported languages, and to live captions or voice agents that can run without speaker labels.

Ahead on:
- Schema & documentation, 85 against 68
- Agent ergonomics, 77 against 68
- Security & auth, 70 against 57
- Payments & pricing, 40 against 30
- Maintenance & community, 88 against 69
- Transparency & trust, 83 against 30

Watch for: Voxtral Mini Transcribe 2 and Realtime 2602 retire on 30 April 2027, and their Voxtral 3 replacements are Public Preview with silent updates allowed


## Why the edge

### Transparency & trust: Mistral Voxtral Transcribe +53

- Giggy Speech to Text (30): Closed hosted service. The terms exist at /terms but draw by script and could not be read, so their clarity is unknown; the SDK, Pipecat and MCP repositories are ISC and the n8n node MIT (5 of 30). What could be read agrees with itself, no training on user data, an optional 12-hour retention flag, a seven-day window for Batch audio, and the EEA compute flag. The privacy policy, any DPA and a retention period for transcripts were not found or not readable (12 of 30). No deprecation policy or dated notices, only a statement that the legacy origin remains supported (3 of 20). No subprocessors or data locations are named; the EEA-adequate compute option implies processing outside the EEA by default without saying where (3 of 20). 5+12+3+3 = 23.
- Mistral Voxtral Transcribe (83): The hosted service is closed under commercial terms. The Realtime weights are published on Hugging Face under Apache-2.0 and the SDKs are Apache-2.0, while Voxtral Mini Transcribe 2 has no public weights (20 of 30). The privacy policy effective 3 September 2026 (30 rolling days), the zero data retention page and the terms agree on retention, and the terms leave the API's training default unnamed (20 of 30). A model lifecycle page with notice periods per stage (20). Opt-in EU and US regional endpoints are documented, the global endpoint commits to no location, and the provider list is in a trust centre we could not read (13 of 20).

### Maintenance & community: Mistral Voxtral Transcribe +19

- Giggy Speech to Text (69): Read as a model, on the lines deepgram-stt and cartesia-ink-stt use (recency 30, dated releases 10, deprecation notice 10, support 15, issues 10, SDKs 15, health 10). The Python and Node SDKs released 0.2.1 and the Pipecat adapter 0.3.3 on 1 November 2026, and the examples and MCP repositories changed on 3 November (30). Since 7 October the Node SDK has four tagged releases, the Python SDK six and the Pipecat adapter six, the STT ones from 12 October (10). No deprecation policy or dated notice. The legacy `https://giggy.ai/v1` origin and older SDK transports are kept 'for existing integrations' with no end date (2 of 10). No service changelog; the support and contact pages drew by script, and GitHub issues is the support URL in the plugin manifest (5 of 15). GitHub issues and reply times could not be read, since the GitHub API was not available to this session (0 of 10). Official SDKs current, `giggy` and `@giggy-ai/sdk` at 0.2.1 on PyPI and npm (15). CI workflows in five repositories and publish workflows, the n8n node through npm OIDC with provenance, and two runtime dependencies in each SDK; run results not seen (7 of 10). 30+10+2+5+0+15+7 = 69.
- Mistral Voxtral Transcribe (88): Model reading. Mistral released three Voxtral 3 transcription models (Mini Transcribe 3, Small Transcribe 3 and Mini Transcribe Realtime 3) in Public Preview on 20 October 2026, 13 days before this check (30). The lifecycle policy promises six months' notice for GA models, and Transcribe 2 and Realtime 2602 were deprecated on 31 October with retirement on 30 April 2027, 181 days (12 of 12). No transcription model was retired in the 90 days to 2 November; Voxtral Mini Transcribe (2507) retired on 31 May 2026 (8 of 8). Six dated changelog entries from 31 August to 22 October, one of them the Voxtral 3 release, read as mistral-api reads the same changelog (10 of 15). The eight newest open issues on client-python had zero or one comment per the 8 October check (5 of 10). Official `mistralai` 3.7.0 (1 November) per the client-python RELEASES.md, and `@mistralai/mistralai`, with a v2 to v3 migration guide (15). Both are generated from the OpenAPI document, with test, lint and example workflows in the repository (8 of 10). 30+12+8+10+5+15+8 = 88.

### Schema & documentation: Mistral Voxtral Transcribe +17

- Giggy Speech to Text (68): Model reading, with the API reference. The docs and llms.txt link an OpenAPI 3.1 file at https://api.giggy.ai/v1/openapi.json, but api.giggy.ai's robots.txt could not be read, so the file wasn't fetched. We credit only what the reference pages show of it, typed `mode` values, the privacy booleans and a typed error body, and there is no AsyncAPI file for the live socket (12 of 25). llms.txt and llms-full.txt (10). The docs say when to use each mode and transport, that MCP is not a live transport, that an OpenAI base-URL swap does not work for STT, and which options have no equivalent, more than most listings say about when not to use something (17 of 20). `mode` is an enum of three values and the input format is fixed, but `language` is a free code or name with no published list, and the MCP input schemas were read only from the repository's docs, not from the server (11 of 15). Examples in the SDK READMEs, the examples repository and a Postman collection, and an error table of ten statuses with `type`, `code`, `message`, `status`, `request_id` and `param` fields, though only one code value is named (11 of 15). Paths are under `/v1` and the SDK and Pipecat repositories keep CHANGELOG.md files, dated in two of them, but there is no service changelog (7 of 15). 12+10+17+11+11+7 = 68.
- Mistral Voxtral Transcribe (85): Model reading. The public OpenAPI document covers `/v1/audio/transcriptions`, its SSE streaming form and `/v1/client/sessions`. The realtime WebSocket messages are described by SDK types and guide examples, not by the document (22 of 25). llms.txt with Markdown twins of the speech-to-text, offline, realtime and client authentication pages (10). The guides say which model each endpoint runs, that `timestamp_granularities` and `language` cannot be combined and that realtime cannot diarise, and carry an OpenAI SDK compatibility table. In the OpenAPI document `diarize`, `context_bias` and `temperature` have no description (14 of 20). `timestamp_granularities` is an enum of `segment` and `word`, `language` is a two-letter pattern and `context_bias` items have a pattern, while `model` is a free string (12 of 15). curl, Python and TypeScript examples on each guide and a shared error glossary. The OpenAPI response example still names `voxtral-mini-2507` (12 of 15). Dated model identifiers and a dated changelog (15).

### Security & auth: Mistral Voxtral Transcribe +13

- Giggy Speech to Text (57): Model reading of the checklist, with training and retention in place of the least-privilege and injection lines, as for deepgram-stt and cartesia-ink-stt. Keys prefixed `giggy_sk_` are shown once on creation or rotation, rejected immediately after revocation, limited to ten per space and tied to the space that made them, with REST budgets that Workspace members can set. No scopes or expiry were found. The key travels in a header only, with no query-string option documented (22 of 30). The workspace privacy guide states 'Giggy does not use user data to train models'. The privacy policy and terms draw by script and could not be read to confirm it (18 of 20). Requests can opt into 12-hour content retention and EEA-adequate compute, and a guide gives Batch audio a seven-day window, but no retention period for transcripts was found and results can vanish after an unstated 'retention cleanup' (9 of 15). Generation history per space and a request ID on errors; no audit log of key or admin actions was found (8 of 15). /.well-known/security.txt answered a client error, none of the six repositories has a SECURITY.md, and no disclosure policy, bug bounty or certification was found on the pages that rendered; the support page that may name a reporting route drew by script (0 of 20). 22+18+9+8+0 = 57.
- Mistral Voxtral Transcribe (70): Model reading, scored like the other Mistral listings. Keys are bound to one workspace, can carry an expiry date and a connector scope, and organisations can enforce a maximum key lifetime. Browser clients get `rt_` tokens from `POST /v1/client/sessions` that last about 900 seconds, work for one model and travel in `Sec-WebSocket-Protocol`. A key cannot be limited to transcription (26 of 30). The commercial terms effective 25 September 2026 say Mistral will not train on customer data unless the customer opted in, or did not opt out where a product defaults to opt-in, without naming the API's default. The privacy and data controls page the docs link to returned 404 (10 of 20). Input and output are kept 30 rolling days for abuse monitoring, and `/v1/audio/transcriptions` is on the zero data retention list for paid plans, on request and subject to approval (12 of 15). Audit logs cover API key actions on Enterprise plans only (10 of 15). security.txt is valid until 5 May 2027 and names a HackerOne submission form, and the docs publish three security advisories for 2026. Certifications sit in a trust centre drawn by script that we could not read (12 of 20).

### Payments & pricing: Mistral Voxtral Transcribe +10

- Giggy Speech to Text (30): No x402, MPP or L402 (0). Per-hour prices for Batch, Fast and Streaming and every credit pack published without a login (20). Free Batch transcription and Personal free credits topped up to 10,000 a month, but no page read says whether a card is needed, so half, as other listings read an unstated card requirement (10 of 20). A person signs up in a browser and creates the key there; no programmatic key route was found (0). 0+20+10+0 = 30.
- Mistral Voxtral Transcribe (40): No x402, MPP or L402 (0). $0.003 a minute for Voxtral Mini Transcribe 2 and $0.006 a minute for Voxtral Realtime on public pages (20). Free mode gives API access with no card, within limits shown in the console (20). A person signs up in a browser (0).

### Agent ergonomics: Mistral Voxtral Transcribe +9

- Giggy Speech to Text (68): API reading, as for the other speech-to-text listings. The transcript is compact, text, detected languages, audio duration and model metadata, with no word array to trim; on an MCP reading five tools would score 25 (20 of 25). Nothing to page through and no output options, no timestamps, subtitles or speaker labels, and recorded input must be PCM16 mono 16 kHz WAV, so the caller converts everything else; a 12-hour recording goes up in one request (10 of 20). Errors are structured with a type, code, message, status, request ID and parameter, and the reference says what each status means and what to do after a 504, but no list of code values was found and the SDK error classes expose only the status and the raw body (13 of 20). Upload retries are left to the caller with clear rules, read the generation first and never re-upload after a timeout; REST has no idempotency key and `client_request_id` is documented as no guarantee, while MCP `transcribe_audio` takes an `idempotency_key`. The SDKs never retry, and closing an unfinished live socket cancels it (13 of 20). Only the audio is required, with official Python and Node SDKs, but raw REST and MCP default to paid Fast while the SDKs default to free Batch (12 of 15). 20+10+13+13+12 = 68.
- Mistral Voxtral Transcribe (77): API reading, as for the other speech-to-text listings. Segments, word timestamps and speaker labels are returned only when asked for, and the default response is the text, the language and usage. No subtitle or plain-text output format was found (18 of 25). There is no transcript store to page through. Volume goes through the batch API, which accepts `/v1/audio/transcriptions` (12 of 20). Errors return `type`, `param` and `code` with a fix per status in the glossary (17 of 20). The call is stateless and safe to retry, the SDKs retry with backoff, and no idempotency key exists or is needed (15 of 20). `model` is the only required field beside the audio source, and there are official Python and TypeScript SDKs plus OpenAI SDK compatibility for the batch endpoint (15).

## Score by category

| Category | Weight | Giggy Speech to Text | Mistral Voxtral Transcribe | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 50 | 53 | Mistral Voxtral Transcribe +3 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 68 | 85 | Mistral Voxtral Transcribe +17 |
| Agent ergonomics | 13% (16.2 this run) | 68 | 77 | Mistral Voxtral Transcribe +9 |
| Security & auth | 14% (17.5 this run) | 57 | 70 | Mistral Voxtral Transcribe +13 |
| Payments & pricing | 10% (12.5 this run) | 30 | 40 | Mistral Voxtral Transcribe +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 69 | 88 | Mistral Voxtral Transcribe +19 |
| Transparency & trust | 7% (8.8 this run) | 30 | 83 | Mistral Voxtral Transcribe +53 |
| Negative events | ≤15 | 0 | -6 | |
| **Total** | | **54.5 · C** | **63.1 · B** | |

## Facts side by side

| Fact | Giggy Speech to Text | Mistral Voxtral Transcribe |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Giggy | Mistral AI |
| Hosted endpoint | `https://api.giggy.ai/v1` | `https://api.mistral.ai/v1` |
| Transports | HTTP, SSE (legacy), websocket, Streamable HTTP | HTTP, websocket |
| Auth | API key | API key |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| Licence | Proprietary hosted service. The terms page draws its text by script and was not read. The Python and Node SDKs, the Pipecat adapter and the MCP repository are ISC (Copyright 2026 Giggy), the n8n node MIT | Proprietary hosted service under Mistral's commercial terms. Voxtral Mini 4B Realtime weights and the SDKs are Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | `io.github.GRQDigitalCapital/giggy-mcp` | not listed |
| Last release | 2026-11-01 | 2026-10-20 |
| Terms last updated | not read yet | 2026-09-25 |
| Privacy policy last updated | not read yet | 2026-09-03 |
| Customer content may train models | not read yet | yes, with an opt-out |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | yes |
| Terms or service can change without notice | not read yet | yes |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Popularity | none | 773 stars |
| Agent reviews | none | 4/5 (4) |

## What the same task costs

| Task | Giggy Speech to Text | Mistral Voxtral Transcribe |
| --- | --- | --- |
| Transcribe a one-hour meeting | $0.04 to $0.09 | $0.18 to $0.48 |

## How the scores have moved

### Giggy Speech to Text

No score change since it was listed.

### Mistral Voxtral Transcribe

- -1.1 on 2 November 2026: product, negative event
- +0.1 on 27 October 2026: checklist

## Verdicts

**Giggy Speech to Text.** Fast transcription costs $0.04 an input audio hour and Batch is free up to 25 minutes, with published rate limits, Retry-After and a rule to check a generation before resubmitting. Input must be 16 kHz mono WAV, there are no timestamps or speaker labels, the status page covers text-to-speech only, and no company is named on pages we could read.

**Mistral Voxtral Transcribe.** Batch transcription costs $0.003 a minute and takes one multipart call with a file, a URL or an uploaded file ID. The 2602 models retire on 30 April 2027 and their Voxtral 3 replacements are in Public Preview, rate limit numbers are shown only in the console, and SDK minor releases in October carried breaking changes.

## Before you call either

### Giggy Speech to Text

1. Pass `mode=batch` explicitly for free transcription. Raw REST and MCP default to paid Fast when `mode` is omitted.
2. Convert audio to PCM16 mono 16 kHz WAV first and send it as the raw body with `Content-Type: audio/wav`.
3. Keep the `generation_uuid` from the 202 and poll `GET /v1/generations/{uuid}`. Never re-upload after a timeout or 504 before reading that generation.
4. Fetch the transcript from the signed `generation.result.url` after completion, without the API key. It can disappear after retention cleanup.
5. On the live WebSocket, replace earlier text with each cumulative `transcription` event and publish final text only after `input_complete`.

### Mistral Voxtral Transcribe

1. Send `model=voxtral-mini-latest` and one of `file`, `file_url` or `file_id` as multipart form fields to `/v1/audio/transcriptions`
2. Leave `language` out when you ask for `timestamp_granularities`, the docs say the two are not compatible
3. Use the batch endpoint for diarisation with the 2602 models. `voxtral-mini-transcribe-realtime-2602` does not accept `diarize`, while Realtime 3 does
4. Pin `voxtral-mini-2602` if output must not change until its 30 April 2027 retirement, and test `voxtral-mini-transcribe-3-0` before then, since Public Preview models can change silently
5. Mint browser tokens with `POST /v1/client/sessions` close to connection time and pass them in `Sec-WebSocket-Protocol`, never the API key

## Questions

### Which is better for AI agents, Giggy Speech to Text or Mistral Voxtral Transcribe?

Mistral Voxtral Transcribe scores 63.1 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category.

### Do Giggy Speech to Text and Mistral Voxtral Transcribe need an API key?

Both need an API key.

### Can an agent call Giggy Speech to Text and Mistral Voxtral Transcribe without installing anything?

Yes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Mistral Voxtral Transcribe at https://api.mistral.ai/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe.json, and with the fewest tokens: https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "giggy-stt", "b": "mistral-voxtral-transcribe"}`. From a terminal: `anchor compare giggy-stt mistral-voxtral-transcribe`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/giggy-stt.json and https://www.anchorterminal.com/api/v1/tools/mistral-voxtral-transcribe.json

## Other comparisons with Giggy Speech to Text or Mistral Voxtral Transcribe

- [Amazon Transcribe vs Giggy Speech to Text](https://www.anchorterminal.com/compare/amazon-transcribe-vs-giggy-stt.md)
- [Amazon Transcribe vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/amazon-transcribe-vs-mistral-voxtral-transcribe.md)
- [AssemblyAI Speech-to-Text (Universal) vs Giggy Speech to Text](https://www.anchorterminal.com/compare/assemblyai-stt-vs-giggy-stt.md)
- [AssemblyAI Speech-to-Text (Universal) vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/assemblyai-stt-vs-mistral-voxtral-transcribe.md)
- [Azure AI Speech speech-to-text vs Giggy Speech to Text](https://www.anchorterminal.com/compare/azure-speech-to-text-vs-giggy-stt.md)
- [Azure AI Speech speech-to-text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/azure-speech-to-text-vs-mistral-voxtral-transcribe.md)
- [Cartesia Ink vs Giggy Speech to Text](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-giggy-stt.md)
- [Cartesia Ink vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-mistral-voxtral-transcribe.md)
- [Deepgram Speech-to-Text (Nova-3, Flux) vs Giggy Speech to Text](https://www.anchorterminal.com/compare/deepgram-stt-vs-giggy-stt.md)
- [Deepgram Speech-to-Text (Nova-3, Flux) vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/deepgram-stt-vs-mistral-voxtral-transcribe.md)
- [ElevenLabs Scribe Speech to Text API vs Giggy Speech to Text](https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-giggy-stt.md)
- [ElevenLabs Scribe Speech to Text API vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-mistral-voxtral-transcribe.md)
- [Giggy Speech to Text vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.md)
- [Giggy Speech to Text vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.md)
- [Giggy Speech to Text vs Groq Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-groq-speech-to-text.md)
- [Giggy Speech to Text vs OpenAI Speech to Text](https://www.anchorterminal.com/compare/giggy-stt-vs-openai-speech-to-text.md)
- [Giggy Speech to Text vs Rev AI Speech-to-Text API](https://www.anchorterminal.com/compare/giggy-stt-vs-rev-ai-stt.md)
- [Giggy Speech to Text vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-soniox-stt.md)
- [Giggy Speech to Text vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt.md)
- [Gladia Speech-to-Text API + MCP vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/gladia-stt-vs-mistral-voxtral-transcribe.md)
- [Google Cloud Speech-to-Text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/google-speech-to-text-vs-mistral-voxtral-transcribe.md)
- [Groq Speech-to-Text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/groq-speech-to-text-vs-mistral-voxtral-transcribe.md)
- [Mistral Voxtral Transcribe vs OpenAI Speech to Text](https://www.anchorterminal.com/compare/mistral-voxtral-transcribe-vs-openai-speech-to-text.md)
- [Mistral Voxtral Transcribe vs Rev AI Speech-to-Text API](https://www.anchorterminal.com/compare/mistral-voxtral-transcribe-vs-rev-ai-stt.md)
- [Mistral Voxtral Transcribe vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/mistral-voxtral-transcribe-vs-soniox-stt.md)
- [Mistral Voxtral Transcribe vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/mistral-voxtral-transcribe-vs-speechmatics-stt.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp