Install Jentic One Beta

Connect the Glasser to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Glasser, 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%2Fglasser.ai%2Fglasser" | 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%2Fglasser.ai%2Fglasser" | 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 Glasser API.

Run company intelligence and web research on a target

Find prospects through people search

Pull keyword and SEO research and social media research

Retrieve market data for a sector or query

Search and inspect runnable endpoints, then start, poll, and stop runs

GET STARTED

Start building with Glasser API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Glasser API for, with concrete tasks.

★ Agent-Run GTM Research

An AI agent assembles a go-to-market brief on a target account without a human stitching tools together. It runs company intelligence and web research, finds prospects through people search, and pulls market data, all from one key. Jentic exposes each Glasser operation with its input schema so the agent supplies the company and query fields correctly on the first call.

Run company intelligence on a domain, find prospects at that company, then pull market data for its sector

Prospect and Company Enrichment

A sales workflow enriches a lead list with company and contact signals before a rep reaches out. The Glasser API runs company intelligence on each domain and people search to surface prospects, and SEO and social research add context on the company's online footprint. The results feed straight into the workflow's own records.

Find prospects at a target company, then run company intelligence and social research to enrich each record

Run Orchestration and Spend Control

A team runs many research calls and needs to watch spend against a prepaid balance. The Glasser API searches and inspects runnable endpoints to see schemas and price, starts and polls runs, and stops any that run long, while the balance and balance-history operations report every movement. Spend stays visible as volume grows.

Inspect a runnable endpoint for its price, start a run, poll its status, and read the balance history to confirm the charge

Key Endpoints

14 endpoints — the glasser api runs go-to-market research through one key and a pay-per-call model, returning company intelligence, web research, prospect search, seo and social research, and market data.

METHOD

PATH

DESCRIPTION

POST

/v1/solutions/gtm/company_intelligence

Run company intelligence on a target

POST

/v1/solutions/gtm/people_search

Find prospects

POST

/v1/solutions/gtm/web_research

Run web research

POST

/v1/solutions/gtm/market_data

Retrieve market data

POST

/v1/runs

Start a run

GET

/v1/runs/{runId}

Get a run's status and output

GET

/v1/balance

Read the current balance

POST

/v1/solutions/gtm/company_intelligence

Run company intelligence on a target

POST

/v1/solutions/gtm/people_search

Find prospects

POST

/v1/solutions/gtm/web_research

Run web research

POST

/v1/solutions/gtm/market_data

Retrieve market data

POST

/v1/runs

Start a run

GET

/v1/runs/{runId}

Get a run's status and output

GET

/v1/balance

Read the current balance

Why Jentic?

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

Setup

Wiring the Glasser API by hand means managing its bearer token, learning the research solution and run endpoints, and watching a prepaid balance as calls draw it down. Through Jentic you install once, import Glasser from the API Directory, store the token once, and your agent calls it.

Permission scoping

Glasser's research and run operations carry their inputs in the request body, so a rule bounds which operations your agent may call, such as company intelligence and market data, not which target. You choose the operations it may call, so the generic run operation and balance movements are not included unless you add them.

Credential isolation

Your Glasser token 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 company intelligence' or 'find prospects', and Jentic returns the matching Glasser operation with its input schema so the agent calls the right endpoint without reading the reference docs.

FAQs

Specific to using Glasser API through Jentic.

What authentication does the Glasser API use?

The Glasser API authenticates with a bearer token in the Authorization header per its OpenAPI spec. Through Jentic that token is stored encrypted by your own Jentic One instance and injected at call time, so it never sits in your agent's prompt or logs.

Can I run company intelligence with the Glasser API?

Yes. The company-intelligence operation takes a target and returns an intelligence result, and you can pair it with web research, people search, and market data from the same key. Each research call draws from your prepaid balance.

What are the rate limits for the Glasser API?

The Glasser OpenAPI spec does not publish fixed rate limits. Glasser is pay-per-call drawn from a prepaid balance, so the balance and balance-history operations let your agent track remaining funds and spend rather than depend on a documented request ceiling.

Is there a Glasser MCP server?

You do not need an MCP server to give your agent the Glasser API. Jentic connects it directly from the API Directory: import it, store your token once, and your agent calls its operations. Operations are discovered on demand, so your agent's context stays lean instead of loading a full tool list up front.

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

Yes. Write a rule that allows only the company-intelligence and market-data research operations, so the agent can run those lookups but cannot start arbitrary runs or move your balance, and every call it makes is logged. The generic run and balance operations stay out of the allowed set until you add them.

How do I run company intelligence with the Glasser API through Jentic?

Search Jentic for 'run company intelligence', and it returns the Glasser company-intelligence operation with its input schema. Your agent posts the target and reads the intelligence result back. To run it on your own infrastructure, install Jentic One from its GitHub repo.

Glasser

AI ReadinessAI-Aware (B-)62/100

See full scorecard

Official vendor OpenAPI document · agent-readyData EnrichmentCompany Databearer14 EndpointsREST

For Agents

Run company intelligence, web research, prospect search, SEO, social, and market-data lookups, orchestrate runs, and track prepaid balance and spend.

Use for: Run company intelligence on a domain, Find prospects at a target company, Get keyword and SEO research for a topic, Retrieve market data for an industry

Not supported: Does not host your own APIs, manage billing accounts, or store business records. Use for running go-to-market research and data lookups across wholesale APIs only.

The Glasser API runs go-to-market research through one key and a pay-per-call model, returning company intelligence, web research, prospect search, SEO and social research, and market data. It also exposes a run layer: search and inspect runnable endpoints with their schemas and price, start a run, poll its status and output, or stop it. A balance endpoint and a full balance history track spend against a prepaid balance.

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).

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.

62%

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

18%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

93%

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: 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: ASignals: 1

80%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Glasser to your agent

Capabilities

Start building with Glasser API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Glasser

Jentic AI Readiness Score

Glasser

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