Install Jentic One Beta

Connect the Moda Data API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Moda Data 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.

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%2Fmoda.dev%2Fmoda" | sh

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%2Fmoda.dev%2Fmoda" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic 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 Moda Data API.

Search agent traces by text, cluster, user, environment, and positive or negative outcome

Run keyword, semantic, or hybrid search over message content and open the surrounding trace context

List hallucination detections filtered by contradicted or verified kind

Break down tool failures by tool name and failure subtype with examples

Review ranked problems with their evidence, affected traces, and investigation reports

GET STARTED

Start building with Moda Data API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Moda Data API for, with concrete tasks.

★ Agent Self-Review Through Jentic

A coding agent working on your production agent pulls the ranked problems Moda has found, opens the evidence and affected traces for the top one, and drafts a fix. Through Jentic the agent finds the problem and trace operations by intent and calls them with a stored x-api-key, then records mark_fixed feedback on the problem once the change ships.

List problems from the last 7 days, fetch the evidence for the top-ranked problem id, then submit feedback with action 'mark_fixed' and a reason

Hallucination and Tool-Failure Monitoring

Teams running LLM agents in production check hallucination detections by kind, contradicted or verified, and drill into tool failures by toolName and subtype to see which integrations break and how. Frustration and emotion detections show where users push back, filterable by user_id or conversation_id.

Get hallucination detections with kind 'contradicted' for the last 30 days and tool-failure detail for the tool 'search_orders'

Trace Search and Debugging

Developers debugging a bad answer search messages with hybrid retrieval, open the returned anchor's context window, and read the trace's step scores and world-state snapshot at the message where it went wrong. Topic clusters group traces by what users asked about, so a whole category of conversations can be reviewed together.

Search messages for 'cancel my subscription' in hybrid mode over the last 7d, then fetch the context for the first result's conversationId

Key Endpoints

32 endpoints — the moda data api gives tenant-scoped access to the production traces of your ai agents and the signals moda derives from them.

METHOD

PATH

DESCRIPTION

GET

/api/v1/data/overview

Get analytics overview

GET

/api/v1/data/conversations

Search traces

GET

/api/v1/data/search

Search message anchors

GET

/api/v1/data/problems

List ranked problems

GET

/api/v1/data/problems/{id}/evidence

List problem evidence

GET

/api/v1/data/hallucinations

Get hallucination detections

GET

/api/v1/data/tool-failures/{toolName}

Get tool-failure detail

POST

/api/v1/data/problems/{id}/feedback

Submit problem feedback

GET

/api/v1/data/overview

Get analytics overview

GET

/api/v1/data/conversations

Search traces

GET

/api/v1/data/search

Search message anchors

GET

/api/v1/data/problems

List ranked problems

GET

/api/v1/data/problems/{id}/evidence

List problem evidence

GET

/api/v1/data/hallucinations

Get hallucination detections

GET

/api/v1/data/tool-failures/{toolName}

Get tool-failure detail

POST

/api/v1/data/problems/{id}/feedback

Submit problem feedback

Why Jentic?

What agents get from Jentic-routed access to this vendor.

Setup

Wiring the Moda Data API by hand means setting the x-api-key header, learning which of its list operations page by offset and which by cursor, and chaining trace ids between search, context, and world-state calls. Through Jentic you install once, import Moda from the API Directory, store the key once, and your agent calls it.

Permission scoping

Moda puts the problem id, conversationId, and toolName in the URL path, so a rule can pin your agent to one problem or one trace and the operations you pick. You choose the operations it may call, so the write operations like problem feedback and custom-signal labels are not included unless you add them.

Credential isolation

Your Moda key 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 'find hallucinations in my agent traces' or 'list my agent's top problems', and Jentic returns the matching Moda operation with its input schema so the agent calls the right endpoint without reading the reference docs.

FAQs

Specific to using Moda Data API through Jentic.

What authentication does the Moda Data API use?

The Moda Data API authenticates with an API key sent in the `x-api-key` header per its OpenAPI spec, declared globally for every operation, and access is scoped to your tenant. Through Jentic the key is stored once, encrypted, by your own Jentic One instance and injected at call time, so it never enters the agent's prompt or logs.

Can I search my agent's traces semantically with the Moda Data API?

Yes. The message search operation takes a q query and a mode of keyword, semantic, or hybrid, with hybrid as the default, plus user_id and time_range filters. It returns anchors you pass to the trace context operation with msg_index to read the surrounding messages.

Can I limit what my agent is allowed to do with the Moda API?

Yes. For example, write a rule that allows only GET requests under /api/v1/data, so the agent can search traces and read problems and detections but cannot submit problem feedback or label custom signals, and every call it makes is logged.

What are the rate limits for the Moda Data API?

The OpenAPI spec does not specify rate limits. Check the Moda documentation at https://moda.dev for current limits; list operations page with limit plus offset or cursor, and several cap limit at 20 or 100 per call.

How do I find my agent's top problems with Moda through Jentic?

Search Jentic for the intent 'list my agent's top problems', which returns the Moda problems operation on /api/v1/data/problems with its input schema; the agent sets days_back and limit, then follows each problem id to its evidence and traces. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Is there a Moda MCP server?

You don't need an MCP server to give your agent the Moda Data API. Jentic connects it directly from the API Directory: import it, store your key once, and your agent calls the trace, detection, and problem operations. Operations are discovered on demand, so no extra tool definitions are loaded into the agent's context.

Moda Data API

AI ReadinessAI-Aware (B)64/100

See full scorecard

Official vendor OpenAPI document · agent-readyDeveloper ToolsMonitoring ObservabilityapiKey32 EndpointsREST

For Agents

Search and analyse your AI agent's production traces with Moda: topic clusters, hallucination, frustration, and tool-failure detections, ranked problems with evidence, and world-state replays. Authenticated with an x-api-key header.

Use for: Find all traces from the last 24 hours with a negative outcome, Search production messages semantically for refund complaints, List the top problems my agent hit this week, Get the evidence behind a specific problem

Not supported: Does not ingest new traces, run LLM prompts, or manage model deployments. Use for reading and triaging the AI agent trace analytics Moda has already collected only.

The Moda Data API gives tenant-scoped access to the production traces of your AI agents and the signals Moda derives from them. You can search traces by text, cluster, user, environment, and outcome, run keyword, semantic, or hybrid search over messages, and open a trace's context, step scores, and world-state replay. Moda surfaces frustration, emotion, hallucination, and tool-failure detections, ranks recurring problems with their evidence and investigation reports, and tracks custom signals you label. Almost every operation is a read; the few writes record problem lifecycle feedback, custom-signal labels, and CLI feedback and telemetry.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

97%

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.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: B-Signals: 4

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.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: D+Signals: 4

46%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

50%

Summary Coverage

Coverage of summaries across operations/tags/info.

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.

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).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: B-Signals: 1

60%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Moda Data API to your agent

Capabilities

Start building with Moda Data API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Moda Data API

Jentic AI Readiness Score

Moda Data API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness