Install Jentic One Beta

Connect the Mencoro API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Mencoro 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%2Fmencoro.com%2Fmencoro" | 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%2Fmencoro.com%2Fmencoro" | 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 Mencoro API.

Read a project's headline visibility metrics over a date window: share of voice, mention, SERP, and shopping rates, and average positions

List the domains and pages AI answers cited for a project, filtered by engines and grouped as needed

Compare the brand head to head against each tracked competitor with the co-occurrence report

Create tracked queries as the cross product of query texts, engines, and countries, up to 100 combinations per call

GET STARTED

Start building with Mencoro API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Mencoro API for, with concrete tasks.

★ Weekly AI-visibility report from an agent through Jentic

A marketing agent compiles a weekly report on how the brand appears in AI answers. Through Jentic it reads project metrics for the last seven days, pulls the biggest movers, and lists the sources AI engines cited, then writes a short summary for the team. The Mencoro key stays in your own Jentic One instance, and a key only ever restricts what its owner's role already allows.

Call GET /api/v1/organizations/{organizationId}/projects/{projectId}/metrics with dateFrom '2026-11-02' and dateTo '2026-11-08', then GET /api/v1/organizations/{organizationId}/projects/{projectId}/metrics/movers for the same window, and summarise share of voice and the top movers

Citation source analysis

To earn mentions in AI answers, content teams need to know which pages the engines cite. The cited-sources report returns the domains and pages AI answers cited for a project over a required date window, filterable by engines such as perplexity or google_ai_overview, so a team can target the publications that shape answers in their category.

Call GET /api/v1/organizations/{organizationId}/projects/{projectId}/cited-sources with dateFrom '2026-10-01', dateTo '2026-10-31', and engines 'perplexity', and list the ten most cited domains

Competitor head-to-head tracking

Brand teams track competitors alongside their own brand inside a project. The co-occurrence report gives the brand's head-to-head record against each tracked competitor in AI answers, and competitors can be added, replaced, or removed per project, so an agent can flag when a rival starts winning answers it used to lose.

Call GET /api/v1/organizations/{organizationId}/projects/{projectId}/competitors to find the competitor id for 'Acme', then GET /api/v1/organizations/{organizationId}/projects/{projectId}/competitors/co-occurrence with that competitorId for the last 30 days

Tracked query setup and maintenance

Tracked queries are created as the cross product of queryTexts, engines, and countries, so three texts on two engines in two countries create twelve queries, with at most 100 combinations per call and checkFrequency, nPasses, queryClusterIds, and an Idempotency-Key required. Batch operations pause, resume, recheck, or change check frequency and passes, and the count endpoint prices checking them before you commit.

Call POST /api/v1/organizations/{organizationId}/projects/{projectId}/tracked-queries with an Idempotency-Key, queryTexts for two prompts, engines chatgpt and perplexity, countries US and GB, checkFrequency 'weekly', nPasses 1, and an empty queryClusterIds list, then read GET /api/v1/organizations/{organizationId}/projects/{projectId}/tracked-queries/count

Key Endpoints

90 endpoints — the mencoro api tracks how a brand shows up in ai answers and search results, across engines such as chatgpt, claude, perplexity, google_ai_overview, google_serp, and google_shopping.

METHOD

PATH

DESCRIPTION

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/metrics

Headline visibility metrics

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/cited-sources

Sources AI answers cited

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/competitors/co-occurrence

Head-to-head competitor record

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/ai-responses

List captured AI answers

POST

/api/v1/organizations/{organizationId}/projects/{projectId}/tracked-queries

Create tracked queries

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/metrics/movers

Queries ranked by metric movement

POST

/api/v1/organizations/{organizationId}/projects/{projectId}/discovery/prompts

Start a prompt discovery job

GET

/api/v1/organizations/{organizationId}/jobs/{jobId}

Get an asynchronous job

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/metrics

Headline visibility metrics

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/cited-sources

Sources AI answers cited

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/competitors/co-occurrence

Head-to-head competitor record

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/ai-responses

List captured AI answers

POST

/api/v1/organizations/{organizationId}/projects/{projectId}/tracked-queries

Create tracked queries

GET

/api/v1/organizations/{organizationId}/projects/{projectId}/metrics/movers

Queries ranked by metric movement

POST

/api/v1/organizations/{organizationId}/projects/{projectId}/discovery/prompts

Start a prompt discovery job

Why Jentic?

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

Setup

Wiring Mencoro by hand means sending a mencoro_sk_ bearer key, generating an Idempotency-Key for every write, running a preview call to get an X-Mencoro-Confirmation for organisation changes, and polling asynchronous discovery jobs. Through Jentic you install once, import Mencoro from the API Directory, store the key once, and your agent calls it.

Permission scoping

Mencoro puts the organisation and project ids in the URL path (/api/v1/organizations/{organizationId}/projects/{projectId}/...), so a rule can pin your agent to one project and the operations you pick. You choose the operations it may call, so destructive ones like archiving a project or bulk-deleting tracked queries are not included unless you add them.

Credential isolation

Your Mencoro API 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 'get share of voice in AI answers' or 'list sources AI engines cited', and Jentic returns the matching Mencoro operation with its input schema, including the required date window, so the agent calls the right endpoint directly.

FAQs

Specific to using Mencoro API through Jentic.

What authentication does the Mencoro API use?

Per its OpenAPI spec, the Mencoro API uses HTTP bearer auth with a Mencoro API key, sent as Authorization: Bearer mencoro_sk_. Keys are created in the app under API keys, shown once, and only ever restrict: a key never grants more than its owner's membership and role allow. Organisation, member, and invitation changes also need an X-Mencoro-Confirmation header from a preview call. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time.

Which AI engines does the Mencoro API track?

The engines filter on the metrics operations includes chatgpt, claude, perplexity, google_ai_overview, google_ai_mode, google_serp, and google_shopping. Pass one or more in engines, with optional countries and queryClusterIds, to narrow metrics such as share of voice, sentiment, and cited sources.

What are the rate limits for the Mencoro API?

The OpenAPI spec does not publish numeric rate limits; it lists rate_limit_exceeded as an error code and returns a requestId to quote when reporting failures. Tracked-query creation is capped at 100 combinations per call. Contact Mencoro via https://mencoro.com/contact/ for current limits.

Is there a Mencoro MCP server?

You don't need an MCP server to give your agent Mencoro. Jentic connects it directly from the API Directory: import it, store your API key once, and your agent discovers the metrics and tracking operations it needs on demand, without loading the whole surface into its context.

How do I read a project's share of voice through Jentic?

Search Jentic for 'get brand share of voice in AI answers', load the GET /api/v1/organizations/{organizationId}/projects/{projectId}/metrics operation, and execute it with the organizationId, projectId, dateFrom, and dateTo, plus optional engines. Positions are 1-based, so lower is better, while rates and share of voice run 0 to 100. To run it on your own infrastructure, install Jentic One from its GitHub repo.

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

Yes. For example, write a rule that allows only GET operations under /api/v1/organizations/{organizationId}/projects/{projectId}/ for one project, so the agent can read metrics, cited sources, and captured answers for that brand but cannot create tracked queries, start discovery jobs, or change members. Every call it makes is logged.

Mencoro API

AI ReadinessAI-Aware (B)67/100

See full scorecard

Official vendor OpenAPI document · agent-readyMarketingSeo Sembearer90 EndpointsREST

For Agents

Read a brand's share of voice, mention rates, positions, sentiment, and cited sources across AI engines and Google results, inspect the captured AI answers, and manage tracked queries, keyword clusters, and competitors in Mencoro projects.

Use for: What is our share of voice in ChatGPT and Perplexity this month, List all sources AI answers cited for our brand last week, Find the tracked queries whose mention rate dropped the most, Check how often we appear next to our main competitor in AI answers

Not supported: Does not publish content, buy ads, or crawl a site for technical SEO issues. Use for tracking brand visibility in AI answers and search results only.

The Mencoro API tracks how a brand shows up in AI answers and search results, across engines such as chatgpt, claude, perplexity, google_ai_overview, google_serp, and google_shopping. Projects hold a brand monitoring profile, tracked competitors, and tracked queries grouped into keyword clusters, and the API returns share of voice, mention, SERP, and shopping rates, average positions, sentiment, cited sources, and the raw captured AI answers over a date window. Discovery jobs suggest keywords, prompts, and brand-name aliases, and organisation, member, and invitation changes go through a preview step that issues a short-lived confirmation.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: ASignals: 4

94%

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).

42%

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: BSignals: 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: C-Signals: 4

49%

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.

58%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: ASignals: 1

87%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: B-Signals: 1

60%

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: A-Signals: 1

79%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Mencoro API to your agent

Capabilities

Start building with Mencoro API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Mencoro API

Jentic AI Readiness Score

Mencoro 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