Install Jentic One Beta
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Happenstance 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%2Fhappenstance.ai%2Fhappenstance" | shStep 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%2Fhappenstance.ai%2Fhappenstance" | 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.
What an agent can do with Happenstance API.
Create a people search and read its results
Ask an existing search to find more matching people
Start an in-depth research job on a person and read it when ready
List the groups a search can run against
Read the current user profile and account usage
GET STARTED
Patterns agents use Happenstance API for, with concrete tasks.
★ Network People Search
An agent finds the right people to reach out to across a user's network. It creates a search from a natural-language description, reads the ranked results, and calls find-more when it needs a deeper pool. Because a search is a stored resource with its own id, the agent can return to the same search and expand it rather than starting over.
Create a search for people matching a description, read the results, and request more matches if fewer than five are returned
Person Research Dossier
An agent builds a research dossier on a person before a meeting. It starts a research job, then reads the research back by its id once it is ready. Keeping research as a separate job lets the agent kick it off and collect the result later instead of blocking on a single long call.
Start a research job on a named person and poll the research endpoint until the result is ready
Usage-Aware Automation
An agent keeps its people-search automation within budget. It reads account usage before launching a batch of searches and picks the group to search against from the available groups. This lets a scheduled agent throttle itself and target the right network instead of searching blindly.
Read account usage and the available groups, then create a search scoped to the chosen group
9 endpoints — the happenstance api searches people across your network and researches individuals in depth.
METHOD
PATH
DESCRIPTION
/v1/search
Create a people search
/v1/search/{search_id}
Read a search and its results
/v1/search/{search_id}/find-more
Find more matches for a search
/v1/research
Start a research job on a person
/v1/research/{research_id}
Read a research job result
/v1/groups
List searchable groups
/v1/search
Create a people search
/v1/search/{search_id}
Read a search and its results
/v1/search/{search_id}/find-more
Find more matches for a search
/v1/research
Start a research job on a person
/v1/research/{research_id}
Read a research job result
/v1/groups
List searchable groups
What agents get from Jentic-routed access to this vendor.
Setup
Wiring Happenstance by hand means handling its bearer token, running searches and research as asynchronous jobs you poll, and watching account usage yourself. Through Jentic you install once, import Happenstance from the API Directory, store the token once, and your agent calls it.
Permission scoping
Happenstance carries search and research ids in the URL path, so a rule can pin your agent to the search operations for one search. You choose the operations it may call, so research and account endpoints are not included unless you add them.
Credential isolation
Your Happenstance 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 'search people in my network' or 'research a person', and Jentic returns the matching Happenstance operation with its input schema so the agent calls the right endpoint without reading the reference docs.
Alternatives and complements available in the Jentic catalogue.
Specific to using Happenstance API through Jentic.
What authentication does the Happenstance API use?
Per its OpenAPI spec, the Happenstance API authenticates with a bearer token sent in the Authorization header. Through Jentic the token is stored by your own self-hosted instance and injected when the agent calls an operation, so it never appears in the agent's prompt or logs.
Can I search for people and run research with the Happenstance API?
Yes. An agent creates a search from a description and reads the ranked results, then calls find-more to widen the pool. Separately it can start a research job on a person and read the research back by its id once it is ready, so discovery and deep research are two distinct flows.
What are the rate limits for the Happenstance API?
The OpenAPI spec does not state a numeric rate limit, but it does expose a usage endpoint an agent can read to track its own consumption. Add retry and backoff around 429 responses, and check the Happenstance documentation at https://developer.happenstance.ai for any published limits.
Can I limit what my agent is allowed to do with the Happenstance API?
Yes. Write a rule that allows the search create and read operations for one search id, so the agent can run and widen a specific search while the research and account operations stay out of reach until you add them, and every call it makes is logged. Happenstance carries search and research ids in the URL path, which is what makes that per-resource boundary possible.
Is there a Happenstance MCP server?
You do not need an MCP server to give your agent the Happenstance API. Jentic connects it directly from the Jentic API Directory: import Happenstance, store your token once, and your agent calls the search and research operations on demand without loading another server's tool definitions into its context.
How do I search for people with the Happenstance API through Jentic?
Search Jentic by intent such as 'search people in my network', and Jentic returns the Happenstance search operation with its input schema so the agent sends the right fields. To run it on your own infrastructure, install Jentic One from its GitHub repo with `curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh`, then add Happenstance from the directory.
For Agents
Search for people across your network, request more matches, run in-depth research on a person, and read groups, profile, and usage.
Use for: Search for people in my network who match a description, Find more matches for a search I already ran, Run deep research on a specific person, Retrieve the results of a research job by its id
Not supported: Does not handle sending outreach, bulk CSV enrichment, or CRM sync. Use for person research and network people search only.
The Happenstance API searches people across your network and researches individuals in depth. An agent creates a search, reads its results, and asks for more matches, or starts a research job on a person and reads it back when ready. It also exposes the current user's profile, the groups a search can run against, and account usage, so an agent can pick the right network to search and track how much it has consumed.
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.
Base layer of spec validity and structural soundness.
Aggregated quality score from linter diagnostics, weighted by severity.
Percentage of `$ref` references that resolve successfully.
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
Structural correctness score based on schema issues using logarithmic dampening.
Clarity, completeness, and ingestion readiness for developers and tooling.
How richly the API is illustrated with examples.
Percentage of examples that conform to their schemas.
Percentage of operations with complete response definitions (success, client error, server error).
Health of API ingestion, bundling, and resolution within Jentic pipelines.
Semantic breadth, depth, and agent comprehension for AI systems.
Coverage of descriptions across API elements.
Coverage of RFC 9457 Problem Details for error responses.
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
Coverage of summaries across operations/tags/info.
Functional utility, complexity comfort, and AI orchestration readiness.
Agent comfort level based on API operational and structural complexity.
Trust, risk posture, and security compliance.
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
Findability, semantic richness, and reasoning readiness.
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>