Google Dialogflow API
Browse all Google APIs44
AI ReadinessFoundational (D)44/100
Official vendor OpenAPI document · agent-readyAI/MLLanguage Modelsoauth263 EndpointsREST
For Agents
Build, test, and operate conversational AI agents - flows, intents, entities, and test cases - for chatbots and voice bots.
Use for: I need to create a new Dialogflow CX agent for a support flow, List all intents in a Dialogflow agent, Run continuous test cases against an agent environment, Compare two agent versions to find behavioural differences
Not supported: Does not handle large language model fine-tuning, raw audio streaming, or contact-center routing - use for Dialogflow CX conversational agent authoring and testing only.
Google Dialogflow is a conversational AI platform for building chatbots, voice bots, and IVR experiences. The CX (v3) API exposes agents, flows, pages, intents, entity types, webhooks, and test cases so teams can author, version, and continuously evaluate sophisticated multi-turn conversations programmatically. It powers contact-center automation, virtual agents, and voice assistants integrated with telephony providers and websites.
Install Jentic One Beta
Connect the Dialogflow API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Dialogflow API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fgoogleapis.com%2Fdialogflow" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fgoogleapis.com%2Fdialogflow" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Dialogflow API.
Author Dialogflow CX agents with structured flows and pages
Define intents and entity types for natural language understanding
Run conversational test cases and calculate intent coverage
Configure webhooks for fulfillment from external services
Deploy agents across environments (draft, staging, production)
Compare agent versions to surface regression risks before deploy
Use Cases
Patterns agents use Dialogflow API for, with concrete tasks.
★ Programmatic Agent Authoring
Engineering teams use the CX API to define agents in code rather than the console - versioning flows, pages, and intents in Git. The agents.create endpoint provisions the shell, then flows.create, pages.create, and intents.create populate the conversational graph. CI pipelines push agent updates and run testCases:calculateCoverage before merging.
Create a Dialogflow CX agent named SupportBot in location us-central1, then create one flow named Triage with two pages and three intents.
Continuous Conversation Testing
Run regression tests against a Dialogflow agent before each deploy. Use environments:runContinuousTest to execute every test case against the latest version, and testCases:calculateCoverage to verify intents and transitions are exercised. Gating deploys on coverage thresholds prevents conversation regressions.
Run continuous tests on environment staging for agent SupportBot, then calculate intent coverage and fail the build if coverage is below 0.8.
Version Comparison Before Deploy
Before promoting a new flow version, call versions:compareVersions to surface what changed in the conversational graph. Reviewers see added or removed intents, transition changes, and response differences side-by-side. The compare output drives change-management approvals.
Compare version 5 against version 4 of flow Triage in agent SupportBot and return a summary of added or modified intents.
Agent-Driven Conversation QA
Through Jentic, an AI agent can search for the runContinuousTest operation, kick it off against a target environment, and summarise failing test cases for a human reviewer. The agent operates with scoped Dialogflow OAuth credentials managed in your Jentic One instance.
Use Jentic to search 'run Dialogflow continuous tests', load the schema, and execute environments:runContinuousTest for environment staging, then list failed test case names.
Key Endpoints
63 endpoints — google dialogflow is a conversational ai platform for building chatbots, voice bots, and ivr experiences.
METHOD
PATH
DESCRIPTION
GET
/v3/{+name}
Get a Dialogflow resource (agent, flow, page, intent) by name
POST
/v3/{+agent}/testCases:calculateCoverage
Calculate test case coverage for an agent
POST
/v3/{+environment}:runContinuousTest
Run continuous test cases against an environment
POST
/v3/{+environment}:deployFlow
Deploy a flow version to an environment
POST
/v3/{+baseVersion}:compareVersions
Compare two versions of a flow
GET
/v3/{+name}
Get a Dialogflow resource (agent, flow, page, intent) by name
POST
/v3/{+agent}/testCases:calculateCoverage
Calculate test case coverage for an agent
POST
/v3/{+environment}:runContinuousTest
Run continuous test cases against an environment
POST
/v3/{+environment}:deployFlow
Deploy a flow version to an environment
POST
/v3/{+baseVersion}:compareVersions
Compare two versions of a flow
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
D
Dialogflow API
- Foundational (D)44/100
56
Foundational Compliance56
Developer Experience & Jentic Compatibility22
AI-Readiness & Agent Experience91
Agent Usability63
Security65
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
56
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: CSignals: 4
26%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
0%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
100%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
56
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: CSignals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
25%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
22
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
88%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
0%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
0%
Summary Coverage
Coverage of summaries across operations/tags/info.
91
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
91%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
63
Security
Trust, risk posture, and security compliance.
Grade: B-Signals: 1
62%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
65
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: BSignals: 1
65%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the Dialogflow API by hand means standing up Google OAuth2 with the right scopes, targeting dialogflow.googleapis.com, and building the resource-path calls yourself for CX agents, environments, and test cases. Through Jentic you install once, import the Dialogflow API from the API Directory, store the OAuth credential once, and your agent calls it.
Permission scoping
Dialogflow puts the resource name in the URL path (/v3/{+agent}, /v3/{+environment}), so a rule can pin your agent to one agent or environment: it can run continuous tests and calculate coverage there and nothing else. You choose the operations it may call, so state-changing ones like deployFlow are not included unless you add them.
Credential isolation
Your Google OAuth credential for Dialogflow is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'run Dialogflow CX regression tests' or 'compare agent versions', and Jentic returns the matching Dialogflow operation with its input schema so the agent calls the right endpoint without browsing the reference docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Dialogflow API through Jentic.
What authentication does the Dialogflow API use?
OAuth 2.0 with the cloud-platform and dialogflow scopes. Through Jentic, OAuth tokens are scoped per agent run and stored encrypted in your Jentic One instance, so service-account JSON keys never enter the agent runtime.
Can I run regression tests on a Dialogflow agent via the API?
Yes. The environments:runContinuousTest endpoint executes all test cases against an agent environment, and testCases:calculateCoverage returns intent and transition coverage so you can gate CI on threshold.
What are the rate limits for the Dialogflow API?
Dialogflow CX enforces per-project quotas: design-time edit operations are limited to 60 per minute per agent, runtime detect-intent calls scale with quota request. Check current quotas in the Google Cloud Console under APIs and Services.
How do I compare two Dialogflow versions through Jentic?
Search 'compare Dialogflow versions', load the schema for v3:compareVersions, then execute it with the base and target version names. Jentic returns the diff payload.
Does Dialogflow API v3 support voice and telephony?
Yes. CX agents can be wired to Google Cloud Telephony or third-party SIP providers, with speech recognition and text-to-speech configured per flow. The API manages the agent definition; runtime audio is handled at the integration layer.
Is the Dialogflow API free?
Dialogflow CX has a paid pricing model based on requests per session-minute, with separate rates for text and audio. Dialogflow ES (v2) is generally cheaper but less capable. Check current pricing in the Google Cloud Console.
Can I limit what my agent is allowed to do with the Dialogflow API?
Yes. Because Dialogflow puts the resource name in the URL path (/v3/{+agent} and /v3/{+environment}), your self-hosted Jentic One instance lets you write rules that pin the agent to a single agent or environment, so it can run continuous tests and calculate test coverage there and nothing else. You decide which operations it may call, so state-changing calls like deployFlow are not included unless you explicitly add them. Because Jentic One is self-hosted, your own rules and stored OAuth credential govern every operation the agent runs.
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