$HEADLESS SYSTEMS
03 / Scorecard / Project & Task Management

Fibery

B
Headless Index
63/100
JAIRF
N/A
Verified
AUG 20, 2026
Methodology v1 · JAIRF v1.0.0

Powered by JAIRF v1.0.0 by Jentic · open methodology at /the-headless-index/methodology

Fibery earns Band B in the Project & Task Management category of The Headless Index, with a thesis-fit score of 63/100. Its strongest dimension is headless operation (14/20); its weakest scored dimension is webhooks and events (10/20). No public OpenAPI specification was found when Fibery was scored, which limits how far an agent can go without human integration work.

Editorial verdict
Fibery is solidly built for programmatic consumption. The Headless Index thesis-fit score of 63/100 lands it in the upper-middle of the index, and JAIRF is recorded as N/A for this vendor because no public OpenAPI specification was reachable for the open-source scorer. In practice, vendors at this tier ship most of the primitives agents need, with one or two surfaces still leaning on documentation rather than discovery, and the rest of this verdict explains where Fibery lands inside that pattern. On the API surface, the question is whether the API is the product or a layer beneath the dashboard. Fibery is unusual: the primary surface is a command API where you POST an array of operations to {account}.fibery.io/api/commands, with a GraphQL endpoint (api.fibery.io/graphql answers on the public host) layered for reads. That composability is a real asset. An agent can drive this product across most practical workflows, with a handful of edges where documentation reading still beats schema discovery. On headless operability: The thing Fibery does that almost nobody else in this category does is expose its own schema as a mutable resource. An agent can issue schema commands (fibery.schema/batch) to create types, fields and relations, then immediately write entities against them, so a whole workspace can be built from code. Views, formulas and automation rules still require the browser.[1] On the MCP and agent-integration axis, which is the fastest-moving criterion in the index: The server at github.com/Fibery-inc/fibery-mcp-server is a genuine first party Python implementation at 29 stars, and the org also maintains a fork of the Docker MCP registry (Fibery-inc/mcp-registry), which suggests distribution was thought about. Momentum is the concern: last commit May 2026, and tool coverage is thin next to what the command API can actually do.[2] Event posture closes the loop: an agent that cannot react to state changes is reduced to polling. Fibery exposes webhooks through its own API (api/webhooks/v2) with subscriptions bound to a type, so a consumer can watch a single entity kind rather than the whole account. Payloads carry before and after field states, which is more useful than a bare identifier. Documentation on signing, retry backoff and replay is sparse, and there is no published event catalogue. Net assessment: Fibery can be operated by agents for the majority of practical workflows. The closest thing to a gap is webhooks and events[3], which integrators should sanity-check against their own use case before committing. Strong fit for agent-driven use cases.
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 intent12/20
scored

Fibery is unusual: the primary surface is a command API where you POST an array of operations to {account}.fibery.io/api/commands, with a GraphQL endpoint (api.fibery.io/graphql answers on the public host) layered for reads. That composability is a real asset. Against it, there is no SDK in any language and no versioning statement, so clients pin nothing.

signals (4)
  • +AI review appliedReviewer: Editorial review on 2026-08-19
  • OpenAPI specNot found across 34 probe paths
  • GraphQL endpointNot discovered (5 probes; project-scoped endpoints require a real project ID)
  • SDKs maintainedNone detected in vendor org
cite (1)
  • ai_review_browser.auth@2026-08-19
Headless operation14/20
scored

The thing Fibery does that almost nobody else in this category does is expose its own schema as a mutable resource. An agent can issue schema commands (fibery.schema/batch) to create types, fields and relations, then immediately write entities against them, so a whole workspace can be built from code. Views, formulas and automation rules still require the browser.

signals (9)
  • +AI review appliedReviewer: Editorial review on 2026-08-19
  • API operations exposedNo OpenAPI spec; operations count unknown
  • ·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@2026-08-19
MCP & agent posture14/20
scored

The server at github.com/Fibery-inc/fibery-mcp-server is a genuine first party Python implementation at 29 stars, and the org also maintains a fork of the Docker MCP registry (Fibery-inc/mcp-registry), which suggests distribution was thought about. Momentum is the concern: last commit May 2026, and tool coverage is thin next to what the command API can actually do.

signals (4)
  • +AI review appliedReviewer: Editorial review on 2026-08-19
  • +Official MCP serverhttps://github.com/Fibery-inc/fibery-mcp-server (29 stars, last commit 99 days ago)
  • ·Community MCP servers2 community MCP repos; top by stars: https://github.com/Fibery-inc/awesome-mcp-servers (2 stars)
  • Agent-friendly SDKsNo TypeScript/JavaScript SDK published (agents commonly run in TS/JS)
cite (1)
  • ai_review_browser.mcp@2026-08-19
Schema observability13/20
scored

There is no OpenAPI document, but the workspace schema is queryable at runtime: a fibery.schema/query command returns every type, field and relation with its holder and cardinality, and the per-account GraphQL endpoint supports introspection. An agent discovers the data model by asking rather than by reading (no prose required). What is missing is a static, versioned artifact.

signals (3)
  • +AI review appliedReviewer: Editorial review on 2026-08-19
  • OpenAPINot discovered across 34 standard probe paths
  • GraphQL introspectionNo GraphQL endpoint discovered (5 probes; some vendors use project-scoped endpoints that require a real project handle)
cite (1)
  • ai_review_browser.schema@2026-08-19
Webhooks & events10/20
scored

Fibery exposes webhooks through its own API (api/webhooks/v2) with subscriptions bound to a type, so a consumer can watch a single entity kind rather than the whole account. Payloads carry before and after field states, which is more useful than a bare identifier. Documentation on signing, retry backoff and replay is sparse, and there is no published event catalogue.

signals (2)
  • +AI review appliedReviewer: Editorial review on 2026-08-19
  • ·Webhook docs pageNot reached by crawler within budget (0 pages crawled). Cannot confirm whether vendor offers webhooks.
cite (1)
  • ai_review_browser.webhooks@2026-08-19
JAIRF · 6 dimensions
JAIRF · N/A

This vendor does not publish a public OpenAPI specification. JAIRF cannot be computed. The Headless Index score and editorial verdict carry the readiness assessment.

No public OpenAPI specification discovered during collection

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FAQ

Fibery and agent readiness

Is Fibery agent-ready?
Fibery scores Band B on The Headless Index. Its JAIRF rating is not available because no machine-readable spec was scored. Its strongest area for agent use is headless operation; its weakest is webhooks and events.
Does Fibery publish an OpenAPI spec?
No published OpenAPI specification was found when Fibery was scored. That caps its JAIRF dimensions and forces agents to rely on documentation or reverse engineering to operate it.
What is Fibery's Headless Index score?
Fibery scores 63/100 on the Headless Index thesis-fit rubric and sits in Band B in the Project & Task Management category. The score weighs API-first design, headless operation, MCP and agent posture, schema observability, and webhooks.