03 / Scorecard / AI Platforms

Together AI

Name: Together AI Agent Readiness Scorecard
Item: Together AI
Rating: 49
Author: Headless Index pipeline (auto)

Headless Index

49/100

JAIRF

73.5/100

AI-Aware

Verified

MAY 21, 2026

Methodology v1 · JAIRF v1.0.0

Editorial verdict

Together AI is partially headless and partly UI-led. The Headless Index thesis-fit score of 49/100 puts it mid-table on the index, and JAIRF v1.0.0 puts it at 73.5/100 (Level 2, AI-Aware). In practice, vendors at this tier are partly machine-consumable: the core flows are reachable through code but several adjacent surfaces still expect a human at a dashboard, and the rest of this verdict explains where Together AI lands inside that pattern. On the API surface, the question is whether the API is the product or a layer beneath the dashboard. Together AI exposes chat completions, embeddings, image generation, fine-tuning, and an inference endpoint product for open-weight models through an OpenAI-compatible API. The integration story is plug-and-play for OpenAI-targeted code, with extensions for batch inference and dedicated endpoints that the standard OpenAI API does not expose.^[1] Schema observability is the related test: can an agent introspect the contract from cold, or does it have to read prose documentation to do so? OpenAI-compatibility carries the chat completions schema; Together-specific endpoints (dedicated endpoints, embeddings on long-context models) are documented in prose. A single canonical OpenAPI URL is not prominently exposed but the SDK code generation implies one exists internally.^[2] An agent can drive parts of this product, but not all of it: integrators should plan for human-in-the-loop checkpoints where the headless surface stops short. On headless operability: Model deployment, fine-tuning jobs, dedicated endpoint provisioning, and account configuration are all API-controllable. The Together CLI and Python SDK cover the operational surface. LoRA fine-tunes and full-weight fine-tunes both run through the same job API.^[3] On the MCP and agent-integration axis, which is the fastest-moving criterion in the index: Together AI has not published a first-party MCP server. OpenAI-compat means downstream agent frameworks integrate without protocol work; Together's bet is on cost and model breadth over agent-protocol authorship.^[4] Event posture closes the loop: an agent that cannot react to state changes is reduced to polling. Inference is synchronous; fine-tuning emits status via polling rather than webhooks. The platform's value sits on the inference and fine-tuning sides, not on eventing. Net assessment: integrators can build agent flows against Together AI, but the rough edge to plan around is MCP posture^[5]. Expect to wrap missing pieces in bespoke glue or accept human-in-the-loop checkpoints. Workable but requires scaffolding.

Verdict by Headless Index pipeline (auto)

// AI-drafted from the evidence layer. Editorial review pending.

Scores

Scorecard detail

Headless Index · 5 sub-criteria

API-first design intent5/20

scored

Together AI exposes chat completions, embeddings, image generation, fine-tuning, and an inference endpoint product for open-weight models through an OpenAI-compatible API. The integration story is plug-and-play for OpenAI-targeted code, with extensions for batch inference and dedicated endpoints that the standard OpenAI API does not expose.

signals (5)

+AI review appliedReviewer: Editorial review on 2026-05-20
+OpenAPI specPublished, 111 operations
·GraphQL endpointDiscovered at https://www.together.ai/graphql, introspection disabled or scoped
·SDKs maintained2 (python); top by stars: togethercomputer/sprocket (1 stars)
+SDK recency2 of 2 SDK repos pushed within 30 days (most recent SDK commit: 2026-05-17)

cite (4)

openapi.url@2026-05-19
graphql.url@2026-05-19
github.sdks@2026-05-19
freshness.most_recent_sdk_commit@2026-05-19

Headless operation16/20

scored

Model deployment, fine-tuning jobs, dedicated endpoint provisioning, and account configuration are all API-controllable. The Together CLI and Python SDK cover the operational surface. LoRA fine-tunes and full-weight fine-tunes both run through the same job API.

signals (9)

+AI review appliedReviewer: Editorial review on 2026-05-20
+API operations exposed111 operations in OpenAPI spec
·Docs pages crawled0 pages (crawler: none)
·Auth schemes documentedAuth documentation page not reached by crawler
·Setup / quickstart docsNot reached by crawler
·Billing docsNot reached by crawler
·Teams / org docsNot reached by crawler
·CLI docsNot reached by crawler
·Schema / data model docsNot reached by crawler

cite (1)

ai_review_browser.topics_found@2026-05-20

MCP & agent posture4/20

scored

Together AI has not published a first-party MCP server. OpenAI-compat means downstream agent frameworks integrate without protocol work; Together's bet is on cost and model breadth over agent-protocol authorship.

signals (4)

+AI review appliedReviewer: Editorial review on 2026-05-20
−Official MCP serverNone found in vendor's GitHub org or the official MCP registry
−Community MCP serversNone found
−Agent-friendly SDKsNo TypeScript/JavaScript SDK published (agents commonly run in TS/JS)

cite (1)

ai_review_browser.pages_fetched@2026-05-20

Schema observability20/20

scored

OpenAI-compatibility carries the chat completions schema; Together-specific endpoints (dedicated endpoints, embeddings on long-context models) are documented in prose. A single canonical OpenAPI URL is not prominently exposed but the SDK code generation implies one exists internally.

signals (3)

+AI review appliedReviewer: Editorial review on 2026-05-20
+OpenAPIPublished at https://docs.together.ai/openapi.yaml (OpenAPI 3.1.0, 111 operations)
·GraphQL introspectionGraphQL endpoint at https://www.together.ai/graphql but introspection is disabled, scoped, or behind authentication

cite (1)

ai_review_browser.schema@2026-05-20

Webhooks & events4/20

scored

Inference is synchronous; fine-tuning emits status via polling rather than webhooks. The platform's value sits on the inference and fine-tuning sides, not on eventing.

signals (2)

+AI review appliedReviewer: Editorial review on 2026-05-20
·Webhook docs pageNot reached by crawler within budget (0 pages crawled). Cannot confirm whether vendor offers webhooks.

cite (1)

ai_review_browser.pages_fetched@2026-05-20

JAIRF · 6 dimensions

FCFoundational Compliance

70/100

Structural validity, standards conformance, and parsability of the OpenAPI specification.

DXJDeveloper Experience & Tooling Compatibility

60.8/100

Documentation clarity, example coverage, response completeness, and ingestion health.

ARAXAI-Readiness & Agent Experience

72.8/100

Semantic clarity, intent expression, datatype specificity, and error standardization.

AUAgent Usability

85.2/100

Operational composability, complexity comfort, navigation affordances, and safety patterns.

SECSecurity

80/100

Authentication strength, transport security, secret hygiene, and OWASP risk posture.

AIDAI Discoverability

67.8/100

Descriptive richness, intent phrasing, workflow context, and registry signals.

Band rationale:C band: scores 40-75 range

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Calibration

How THI compares to external scorers

Source	Score	Measures	Last checked
Fern Agent Score	not found	Documentation completeness and SDK shape (~22 checks)	—
CLIRank Agent Friendliness	not found	CLI readiness, docs quality, and overall agent affordances	—
Cloudflare Is It Agent Ready?	blocked	Cloudflare's manual agent-readiness heuristic per vendor URL	—
Jentic Scorecard	—	JAIRF-based scorecard requiring a public OpenAPI specification	—

THI 49 vs external median 0

No external scores available to calibrate against.

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