AWS Amazon Mechanical Turk
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AI ReadinessAI-Aware (B-)60/100
Agent-ready OpenAPI document · curated by JenticAI/MLMl Inferencehmac39 EndpointsREST
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For Agents
Publish, manage and review human-completed tasks (HITs) on Amazon Mechanical Turk - create HITs, approve or reject assignments, manage worker qualifications, and pay bonuses.
Use for: Publish a new HIT for image classification with a $0.10 reward, List all my HITs that are still Assignable, Approve all submitted assignments for HIT id 3ABCXYZ, Reject an assignment with feedback for the worker
Not supported: Does not handle Worker-side task completion, payment processing outside MTurk, or hosting custom HIT UIs - use for the Requester lifecycle of HITs, assignments, qualifications, and bonuses only.
Jentic publishes the only available OpenAPI specification for Amazon Mechanical Turk, keeping it validated and agent-ready. Mechanical Turk (MTurk) is AWS's human-in-the-loop crowdsourcing platform - Requesters publish Human Intelligence Tasks (HITs), Workers complete them, and Requesters review the resulting Assignments. The 39 endpoints cover the full Requester lifecycle: CreateHIT and CreateHITWithHITType, ListHITs, accept/reject Assignments, send bonuses, manage Qualifications and QualificationRequests, and notify or block Workers.
Install Jentic One Beta
Connect the Amazon Mechanical Turk to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Amazon Mechanical Turk, 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%2Famazonaws.com%2Famazon-mechanical-turk" | 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%2Famazonaws.com%2Famazon-mechanical-turk" | 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 Amazon Mechanical Turk API.
Publish Human Intelligence Tasks (HITs) with title, description, reward, lifetime, and assignment count
Create reusable HITTypes with shared properties for batches of similar tasks
List and review submitted Assignments and approve, reject, or send back to Workers
Pay performance bonuses to Workers and notify them of incentives
Define Qualifications and grant or revoke them to gate sensitive HITs to a vetted Worker pool
Block and unblock individual Workers from a Requester's HITs
Update an existing HIT's expiration, review policy, or maximum assignments without recreating it
Use Cases
Patterns agents use Amazon Mechanical Turk API for, with concrete tasks.
★ Crowdsource Labels for Machine Learning Training Data
ML teams need labelled image, text or audio data to train supervised models. Mechanical Turk lets a Requester publish HITs with custom HTML/QuestionForm content, set a per-assignment reward and lifetime, and collect responses from a global Worker pool. The CreateHIT and ListAssignmentsForHIT endpoints, combined with QualificationRequirements, support producing high-quality labelled datasets at low unit cost.
Call CreateHIT with Title='Label image content', Reward='0.10', LifetimeInSeconds=86400, MaxAssignments=3 and a QuestionForm XML, then poll ListAssignmentsForHIT and approve qualifying responses
Build a Vetted Worker Pool With Custom Qualifications
Sensitive or domain-specific tasks (medical text annotation, multilingual transcription) require Workers with verified skills. MTurk's Qualifications API lets a Requester define a custom QualificationType, grant it via QualificationRequest review or a built-in Qualification test, and then require it on subsequent HITs. The agent can review pending QualificationRequests and accept or reject them based on a custom rubric.
Call CreateQualificationType, then list pending requests with ListQualificationRequests and call AcceptQualificationRequest for those who pass a rubric check
Run a Human-in-the-Loop Validation Step
Generative AI pipelines often need a human review step on uncertain model outputs. An agent can take low-confidence outputs from a model, publish them as small HITs (each Assignment shows two model outputs and asks a Worker to pick the better one), and feed the resulting human preferences back into reward modelling. The same primitives - CreateHIT, list assignments, approve, bonus - drive both data labelling and HITL validation.
Call CreateHITWithHITType for each low-confidence output using a pre-built HITType, collect assignments, and aggregate Worker preferences for a feedback dataset
AI Agent Integration for Crowdsourced Workflows
Through Jentic, an AI agent can orchestrate the full Requester lifecycle on Mechanical Turk - publish HITs, list and review assignments, pay bonuses, manage worker pools - without writing custom boto3 logic. Jentic returns the input schema for each MTurk operation and brokers SigV4 credentials so an LLM can drive crowdsourcing workflows from natural-language instructions.
Resolve the intent 'publish a Mechanical Turk HIT' via Jentic search, load the CreateHIT schema, and execute it with title, reward, lifetime, max assignments and a QuestionForm body
Key Endpoints
39 endpoints — jentic publishes the only available openapi specification for amazon mechanical turk, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.CreateHIT
Publish a new Human Intelligence Task
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.ListHITs
List the Requester's HITs with paging
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.ApproveAssignment
Approve a submitted assignment and pay the Worker
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.RejectAssignment
Reject an assignment with feedback
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.SendBonus
Send a bonus payment to a Worker
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.CreateQualificationType
Create a custom qualification type
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.AcceptQualificationRequest
Approve a Worker's qualification request
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.CreateHIT
Publish a new Human Intelligence Task
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.ListHITs
List the Requester's HITs with paging
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.ApproveAssignment
Approve a submitted assignment and pay the Worker
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.RejectAssignment
Reject an assignment with feedback
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.SendBonus
Send a bonus payment to a Worker
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.CreateQualificationType
Create a custom qualification type
POST
/#X-Amz-Target=MTurkRequesterServiceV20170117.AcceptQualificationRequest
Approve a Worker's qualification request
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.
A
Amazon Mechanical Turk
- AI-Aware (B-)60/100
99
Foundational Compliance63
Developer Experience & Jentic Compatibility36
AI-Readiness & Agent Experience94
Agent Usability50
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
99
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: A+Signals: 4
96%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
100%
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.
63
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: B-Signals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
50%
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.
36
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: FSignals: 4
45%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
0%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
50
Security
Trust, risk posture, and security compliance.
Grade: C-Signals: 1
50%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
100
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A+Signals: 1
100%
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 Mechanical Turk Requester API by hand means implementing AWS SigV4 signing, targeting the regional host such as mturk-requester.us-east-1.amazonaws.com, and shaping QuestionForm XML plus your own assignment polling and backoff. Through Jentic you install once, import Amazon Mechanical Turk from the API Directory, store the AWS access key once, and your agent calls it.
Permission scoping
MTurk carries HIT and assignment ids in the request body rather than the URL path, so scoping is by operation, not by path prefix. Limit the agent to the operations it needs, such as CreateHIT and ApproveAssignment, so ones like RejectAssignment or DeleteHIT are not included unless you add them.
Credential isolation
Your AWS access key is stored once, encrypted, by your own Jentic One instance and used to sign each MTurk request with SigV4 at execution time. The raw secret never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'publish a Mechanical Turk HIT' or 'list MTurk assignments', and Jentic returns the matching MTurk operation such as CreateHIT with its input schema so the agent calls the right endpoint without browsing the AWS reference.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Amazon Mechanical Turk API through Jentic.
Why is there no official OpenAPI spec for Amazon Mechanical Turk?
AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Amazon Mechanical Turk via structured tooling. It is validated against the live API and kept up to date. Get started with Jentic One, the self-hosted execution layer.
What authentication does the Mechanical Turk Requester API use?
The MTurk Requester API is signed with AWS Signature Version 4 using IAM access keys. Through Jentic, those AWS credentials live in your Jentic One instance and are used to sign each MTurk request on the agent's behalf - the raw access key never reaches the agent.
Can I create a HIT with custom HTML or external page content?
Yes. CreateHIT accepts either a Question (XML - QuestionForm or HTMLQuestion) describing the task content directly, or an HITLayoutId pointing at a published layout. HTMLQuestion can iframe an externally hosted page for richer interfaces such as bounding-box image annotation.
What are the rate limits for Mechanical Turk?
MTurk enforces per-Requester throttling on the control plane; specific TPS values are not published in the spec. Treat throttling as expected, especially for ListAssignmentsForHIT during bulk reviews, and apply exponential backoff between calls.
How do I approve a batch of assignments through Jentic?
Use the Jentic search query 'list MTurk assignments', load ListAssignmentsForHIT, then for each Submitted assignment call ApproveAssignment with the AssignmentId and an optional RequesterFeedback string. Jentic signs each request with SigV4 against your stored AWS credentials.
Is Mechanical Turk free?
MTurk charges a fee on top of each Worker reward and bonus payment, with higher fees for HITs that require custom Qualifications. There is no charge for control-plane API calls themselves, but a Requester account must be funded to publish paid HITs.
Can I limit what my agent is allowed to do with the Amazon Mechanical Turk API?
Yes. Because you run Jentic One yourself, your own rules decide which MTurk operations and AWS credentials the agent may use. Since MTurk carries HIT and assignment ids in the request body rather than the URL path, scoping is done per operation rather than by path prefix: you can allow only the operations the agent needs, such as CreateHIT and ApproveAssignment, so operations like RejectAssignment or DeleteHIT are not included unless you add them. The AWS access key is signed into each request by your instance at execution time and never reaches the agent.
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