Fiddler Labs

Fiddler Labs (Fiddler AI) is an enterprise AI Observability and Security platform that provides unified visibility, context, and control across AI agents, LLM and GenAI applications, and traditional ML models. The Fiddler platform delivers standardized telemetry, evaluation, continuous monitoring, real-time guardrails, and auditable governance from development through production. Developers integrate through a REST API (v3), an official Python client (fiddler-client), framework SDKs (LangChain, LangGraph, OpenTelemetry, Google ADK, Strands, Evals), and a hosted Model Context Protocol (MCP) server that exposes GenAI observability data to AI assistants. Capabilities include model and application onboarding, production event ingestion, drift and integrity detection, custom metrics, segments, alerting, explainability, LLM gateway routing, and trace/span-level agentic observability.

Fiddler Labs is listed with 1 API on the APIs.io network. Tagged areas include Company, AI Observability, ML Monitoring, LLM Observability, and AI Agents.

The Fiddler Labs catalog on APIs.io includes 1 event-driven AsyncAPI specification.

Fiddler Labs’ developer surface includes documentation, API reference, getting-started guide, engineering blog, pricing, signup flow, authentication, and 24 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

62.8/100 strong ▬ flat Agent 29/100 agent ready Heartbeat 73/100 slowing saas Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemiumSelf serve⚡ Free to try

1 API 1 MCP Servers

Company AI Observability ML Monitoring LLM Observability AI Agents AI Security AI Governance Model Monitoring Explainability Guardrails

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 62.8/100 · strong

Contract Quality 8.3 / 21

Developer Ergonomics 11.3 / 17

Access Clarity 17.0 / 17

Operational Transparency 7.3 / 11

Contract Governance 1.9 / 10

Discoverability 5.8 / 9

Regulatory Posture 4.4 / 15

Agent readiness — 29/100 · agent ready

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 8 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 6 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document
Delegated User Identity +6 pts — a served discovery document listing authorization_code in grant_types_supported (served), else an oauth2 authorizationCode flow or openIdConnect declared in an OpenAPI (documented)

7 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 39.0 — up to +15.3 composite points
Contract Governance scores 18.2 — up to +9.8 composite points
Developer Ergonomics scores 66.7 — up to +6.7 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/fiddler-labs/apis.yml: open an issue on github.com/api-evangelist/fiddler-labs to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
MLOps and AI/ML Infrastructure (LF AI & Data, MLPerf, Kubeflow)	undeclared	-	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

Model Context Protocol (MCP)

measured — observed by APIs.io (documented)

APIs 1

Individual APIs this provider publishes, each with its own machine-readable definition.

Fiddler REST API

The Fiddler REST API (v3) is organized around resource-oriented URLs with JSON request/response bodies, Bearer-token authentication, and standard HTTP verbs and status codes. Re...

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Fiddler Labs MCP Server

Remote MCP server over HTTP.

MCP SERVER

Fiddler Labs API pricing

Prices published by Fiddler Labs, read 2026-10-28 from www.fiddler.ai/pricing. A free plan or tier is listed.

Plan	Price
Free	Free Includes: Real-time guardrails to detect harmful exposure; protects against hallucinations, Toxicity, PII/PHI,
Developer	$0.002 per trace Includes: Everything in Free, plus unified AI observability, custom evaluators, visualization-driven insights,
Enterprise	Contact sales Includes: Everything in Developer, plus enterprise-grade guardrails, scalability, flexible deployment: SaaS, V

Plan details, limits and sources →

Rate limits

: minute
: day

Rate-limit details →

Billed by: trace · FinOps profile →

Pricing Plans 1

Published pricing tiers and plan structures.

Fiddler Labs Plans Pricing

3 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Fiddler Labs Rate Limits

2 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Fiddler Labs Finops

FINOPS

Event Specifications 1

AsyncAPI definitions for this provider's event-driven and streaming APIs.

Fiddler Labs Webhooks

ASYNCAPI

Security Posture 3

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Fiddler Labs Authentication

http · 1 scheme

SECURITY

Fiddler Labs Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Fiddler Labs Trust Center

SOC 2, HIPAA

SECURITY

Resources

Get Started 4

Portal, sign-up, and the first successful call

DeveloperPortal

GettingStarted

SignUp

Sandbox

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

LLMsTxt

LLMsTxt

Design & Contract 5

Pagination, idempotency, versioning, errors, and events

Conventions

Lifecycle

ErrorCatalog

Conformance

Webhooks

Build 3

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Packages

Packages

SDKs

SDKs

Access & Security 5

Authentication, authorization, and security posture

TrustCenter

DomainSecurity

Security

Compliance

Authentication

Operate 3

Status, limits, changes, and where to get help

RateLimits

RateLimits

Deprecation

Deprecation

ChangeLog

ChangeLog

Commercial 4

Pricing, plans, and the legal terms of use

Plans

Pricing

TermsOfService

PrivacyPolicy

Company 3

The organization behind the API

BlogRSS

BlogRSS

Website

Website

Blog

Blog

Source (apis.yml)

aid: fiddler-labs
name: Fiddler Labs
description: Fiddler Labs (Fiddler AI) is an enterprise AI Observability and Security platform that provides unified visibility,
  context, and control across AI agents, LLM and GenAI applications, and traditional ML models. The Fiddler platform delivers
  standardized telemetry, evaluation, continuous monitoring, real-time guardrails, and auditable governance from development
  through production. Developers integrate through a REST API (v3), an official Python client (fiddler-client), framework
  SDKs (LangChain, LangGraph, OpenTelemetry, Google ADK, Strands, Evals), and a hosted Model Context Protocol (MCP) server
  that exposes GenAI observability data to AI assistants. Capabilities include model and application onboarding, production
  event ingestion, drift and integrity detection, custom metrics, segments, alerting, explainability, LLM gateway routing,
  and trace/span-level agentic observability.
url: https://raw.githubusercontent.com/api-evangelist/fiddler-labs/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- bloomberg-beta
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  gated: none
  gated_source:
  - onboarding
  label: Freemium · Self-serve signup
  confidence: high
  source:
  - plans
  - authentication
  - rate-limits
  - security
  - sandbox
  generated: '2026-11-06'
  method: derived
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
image: ''
x-docs-platform: mintlify
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-10-03
tags:
- Company
- AI Observability
- ML Monitoring
- LLM Observability
- AI Agents
- AI Security
- AI Governance
- Model Monitoring
- Explainability
- Guardrails
tags_raw:
- Company
- AI Observability
- ML Monitoring
- LLM Observability
- Agentic AI
- AI Security
- AI Governance
- Model Monitoring
- Explainability
- Guardrails
apis:
- name: Fiddler REST API
  description: The Fiddler REST API (v3) is organized around resource-oriented URLs with JSON request/response bodies, Bearer-token
    authentication, and standard HTTP verbs and status codes. Resource groups include Projects, Models, Applications, Events,
    Spans, Jobs, Baselines, Segments, Custom Metrics, Alert Rules, Environments, Explainability, Evals & Evaluators, Experiments,
    Queries, FQL Expressions, LLM Gateway, File Upload, and Users & Access Keys.
  humanURL: https://docs.fiddler.ai/api
  baseURL: https://app.fiddler.ai/v3
  properties:
  - type: Documentation
    url: https://docs.fiddler.ai/api
  - type: APIReference
    url: https://docs.fiddler.ai/api/rest-api/rest-api
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Plans
  url: plans/fiddler-labs-plans-pricing.yml
- url: https://www.fiddler.ai/blog/rss.xml
  type: BlogRSS
- type: TrustCenter
  url: security/fiddler-labs-trust-center.yml
- type: DomainSecurity
  url: security/fiddler-labs-domain-security.yml
- type: Website
  url: https://www.fiddler.ai/
- type: DeveloperPortal
  url: https://docs.fiddler.ai/
- type: Documentation
  url: https://docs.fiddler.ai/
- type: APIReference
  url: https://docs.fiddler.ai/api
- type: GettingStarted
  url: https://docs.fiddler.ai/first-steps/getting-started-with-agentic-monitoring
- type: Blog
  url: https://www.fiddler.ai/blog
- type: GitHubOrganization
  url: https://github.com/fiddler-labs
- type: Pricing
  url: https://www.fiddler.ai/pricing
- type: SignUp
  url: https://www.fiddler.ai/trial
- type: TermsOfService
  url: https://www.fiddler.ai/terms-of-service
- type: PrivacyPolicy
  url: https://www.fiddler.ai/privacy-policy
- type: Security
  url: https://www.fiddler.ai/security
- type: Compliance
  url: https://www.fiddler.ai/security
- type: Authentication
  url: authentication/fiddler-labs-authentication.yml
- type: Conventions
  url: conventions/fiddler-labs-conventions.yml
- type: RateLimits
  url: rate-limits/fiddler-labs-rate-limits.yml
- type: Lifecycle
  url: lifecycle/fiddler-labs-lifecycle.yml
- type: Deprecation
  url: https://docs.fiddler.ai/changelog
- type: ChangeLog
  url: changelog/fiddler-labs-changelog.yml
- type: ErrorCatalog
  url: errors/fiddler-labs-error-codes.yml
- type: Conformance
  url: conformance/fiddler-labs-conformance.yml
- type: Packages
  url: packages/fiddler-labs-packages.yml
- type: SDKs
  url: packages/fiddler-labs-packages.yml
- type: MCPServer
  url: mcp/fiddler-labs-mcp.yml
- type: LLMsTxt
  url: llms/fiddler-labs-llms.txt
- type: Sandbox
  url: sandbox/fiddler-labs-sandbox.yml
- type: Webhooks
  url: asyncapi/fiddler-labs-webhooks.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

Fiddler Labs API — frequently asked questions

Does Fiddler Labs have an API?

Yes. APIs.io lists 1 API from Fiddler Labs, including Fiddler REST API.

How do I authenticate with the Fiddler Labs API?

Fiddler Labs uses bearer-token authentication (http · 1 scheme). The details are profiled on APIs.io as Fiddler Labs Authentication.

How much does the Fiddler Labs API cost?

Fiddler Labs publishes its prices; its Developer plan is $0.002 per trace as of 2026-10-28. APIs.io lists 3 pricing plans for Fiddler Labs, with each plan's price, limits and inclusions under Pricing on this page.

Does Fiddler Labs have an MCP server?

Yes. APIs.io lists 1 MCP server for Fiddler Labs: Remote MCP server over HTTP.

Is the Fiddler Labs API ready for AI agents?

Fiddler Labs has a Kin Score of 62.8 out of 100 (strong) and an Agent Readiness score of 28.6 (agent-ready), scored by API Evangelist on 2026-11-06.

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get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
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