canonical: https://jentic.com/apis/mencoro.com/mencoro

# Mencoro API

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.

## For AI 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.

## Scope

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.

## Capabilities

- 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
- Pause, resume, force-check, or change the check frequency of tracked queries in batches
- Start keyword, prompt, and brand discovery jobs and poll their results as asynchronous jobs
- Inspect captured AI answers, search snapshots, and shopping snapshots for a tracked query

## Use cases

### 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.

Example prompt: 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.

Example prompt: 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.

Example prompt: 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.

Example prompt: 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

| 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 |

## Key resources

- **Organizations** — Accounts holding projects, members, invitations, plan entitlements, and subscription
- **Projects** — A brand monitoring profile with competitors, tracked queries, and keyword clusters
- **Tracked queries** — Query text, engine, and country combinations checked on a frequency
- **Metrics** — Share of voice, mention rates, positions, sentiment, movers, and time series
- **Captured answers** — AI responses, search snapshots, and shopping snapshots behind the metrics
- **Jobs** — Asynchronous discovery and clustering jobs

## AI readiness

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.

- **Score:** 67 / 100
- **Maturity:** AI-Aware
- **Dimensions:**
  - Foundational Compliance: 84 / 100
  - Developer Experience & Jentic Compatibility: 63 / 100
  - AI-Readiness & Agent Experience: 52 / 100
  - Agent Usability: 87 / 100
  - Security: 60 / 100
  - AI Discoverability: 79 / 100
- **View full report:** https://jentic.com/apis/mencoro.com/mencoro/scorecard
- **How the score is calculated:** https://docs.jentic.com/reference/api-readiness-framework/overview/
- **More about the dimensions:** https://docs.jentic.com/reference/api-readiness-framework/specification/#dimensional-model-overview

### Score it yourself

Every API in the directory is allowlisted, so you can re-score it with no key required.

- **Score your own API:** https://jentic.com/scorecard.md
- **Scoring CLI agent skill:** https://github.com/jentic/jentic-api-scorecard/blob/main/skills/jentic-api-scorecard/SKILL.md

```sh
npx @jentic/api-scorecard-cli score <openapi-url>
```

## Why Jentic

- **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 handling:** 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.
- **Discovery method:** 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.

## Related APIs

- **Semrush API** — Keyword, domain, and backlink data for classic search engine optimisation
- **Ahrefs API** — Backlink, keyword, and site-ranking data for SEO teams
- **Moz API** — Domain authority and link metrics for sites

## FAQ

### 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.