Install Jentic One Beta

Connect the Neurobird Search API to your agent

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

Search the live web and get ranked results with the relevant passages already extracted, at a search_depth of basic, standard, or advanced

Narrow a search by topic such as news, code, science, or finance, and by include_domains, exclude_domains, country, language, or time_range

Generate a grounded answer with include_answer and have verify_quotes check every supporting quote against its source

Stream each stage of the retrieval pipeline as server-sent events while a search runs

GET STARTED

Start building with Neurobird Search API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use Neurobird Search API for, with concrete tasks.

★ Research agent with grounded web answers

A research agent answering a factual question needs current sources, not model memory. Through Jentic the agent searches for 'search the web', loads the Neurobird search operation with its input schema, and posts a query with include_answer and verify_quotes enabled. The response carries ranked results with their relevant passages already extracted, so the agent usually skips a follow-up fetch, plus an answer whose quotes were checked against the source text. The Neurobird key is attached by your own Jentic One instance at call time.

Call POST /v1/search with query 'EU AI Act enforcement timeline', topic 'news', search_depth 'advanced', include_answer true, and verify_quotes true, then report the answer with its sources

Clean page extraction for downstream processing

A summarization pipeline needs the article body of a list of links without navigation, adverts, or boilerplate. The extract operation fetches one or more URLs and returns the main content as markdown or plain text, converting PDFs to text, and it costs one credit per page.

Call POST /v1/extract with urls containing two article links and format 'markdown', then summarize each result

Drop-in replacement for a Tavily client

A developer already using Tavily wants to compare results or costs. Because Neurobird's request and response shapes match Tavily, the existing client switches by pointing at https://search.neurobird.com and sending a Neurobird key. Credits are 1 for a basic or standard search and 2 for an advanced one, with a grounded answer or structured extraction adding 1.

Send the same query to POST /v1/search with search_depth 'basic', then call GET /v1/usage to read the credits consumed

Watching retrieval progress live

An interface that shows users what the agent is doing streams the search instead of waiting for the whole result. The streaming operation emits each pipeline stage as it completes, from engine results to fetched pages and ranked passages, over server-sent events.

Call POST /v1/search/stream with query 'best open source vector databases 2026' and relay each stage event to the user as it arrives

Key Endpoints

27 endpoints — the neurobird search api searches the live web for ai agents in a single call: it fans a query out across many search engines, fuses the rankings with reciprocal rank fusion, fetches and extracts the top pages, and ranks the passages inside them.

METHOD

PATH

DESCRIPTION

POST

/v1/search

Search the web

POST

/v1/search/stream

Search with streamed stages

POST

/v1/extract

Extract clean page content

POST

/v1/keys

Create a free API key

GET

/v1/usage

Usage for the calling key

GET

/v1/billing/balance

Credit balance for the calling key

GET

/v1/billing/packages

Credit packs and request costs

POST

/v1/search

Search the web

POST

/v1/search/stream

Search with streamed stages

POST

/v1/extract

Extract clean page content

POST

/v1/keys

Create a free API key

GET

/v1/usage

Usage for the calling key

GET

/v1/billing/balance

Credit balance for the calling key

GET

/v1/billing/packages

Credit packs and request costs

Why Jentic?

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

Setup

Wiring Neurobird by hand means minting an nbs- key, choosing between bearer and x-api-key headers, telling free search routes apart from the x402 paid route, and handling server-sent events for streamed search. Through Jentic you install once, import Neurobird from the API Directory, store the key once, and your agent calls it.

Permission scoping

Neurobird carries the query and URLs inside the request body, so rules bound which operations your agent may call, not what it searches for. Limit the agent to the operations it needs, such as search and extract, so spending ones like card or crypto checkout are not included unless you add them.

Credential isolation

Your Neurobird 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 'search the web' or 'extract a page as markdown', and Jentic returns the matching Neurobird operation with its input schema so the agent sets search_depth and filters correctly.

FAQs

Specific to using Neurobird Search API through Jentic.

What authentication does the Neurobird Search API use?

Per its OpenAPI spec, Neurobird keys look like nbs- followed by the key and are sent as a bearer token in the Authorization header, or in an `x-api-key` header for clients that prefer it. Usage, credit balance, and checkout operations use the key, while the search, extract, key creation, packages, payments, and health operations are declared with no security requirement. The paid search variant can instead be paid per call with x402 or MPP. Through Jentic your key is stored encrypted by your own instance and attached per call.

Can I get an answer with verified quotes from the Neurobird Search API?

Yes. Set include_answer on POST /v1/search to have Neurobird write an answer from the ranked passages, and set verify_quotes to check each supporting quote back against its source text. A grounded answer adds 1 credit to the cost of the search.

What are the rate limits for the Neurobird Search API?

The spec prices requests in credits rather than stating request-rate ceilings: a free key from POST /keys carries 1,000 free credits a month, a basic or standard search costs 1 credit, an advanced search 2, and /extract 1 per page. It notes the keyless evaluation path is throttled. GET /v1/usage and GET /v1/billing/balance report what your key has used and has left.

Is there a Neurobird MCP server?

Yes - Neurobird offers a hosted MCP server at POST /mcp exposing web_search and extract_url. You can also connect the Neurobird Search API directly through Jentic: your agent gets the full 27-endpoint surface without loading another server's tool definitions into its context, your key is injected at call time by your self-hosted instance instead of living in an MCP config, and your rules decide which operations the agent may call.

How do I search the web with Neurobird through Jentic?

Import Neurobird from the API Directory in your Jentic One instance and store your nbs- key. Your agent searches Jentic for 'search the web', loads POST /v1/search, and sends a query with options such as topic, max_results, and include_domains. 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 Neurobird Search API?

Yes. Write a rule that allows only POST /v1/search and POST /v1/extract, and the agent can search and read pages but cannot start a card or crypto checkout or call the per-call paid search route. Every call it makes is logged.

Neurobird Search API

AI ReadinessAI-Aware (B-)62/100

See full scorecard

Official vendor OpenAPI document · agent-readyData EnrichmentData Transformationbearer, apiKey27 EndpointsREST

For Agents

Search the live web with ranked, pre-extracted passages and optional quote-checked answers, stream each retrieval stage, and extract clean markdown from URLs.

Use for: Search the web for the latest news on EU AI regulation, I need an answer with quotes checked against their sources, Find code examples for parsing SSE in Python from GitHub only, Extract the article text from this URL as markdown

Not supported: Does not crawl entire sites, host a private document index, or generate embeddings. Use for live web search and page extraction only.

The Neurobird Search API searches the live web for AI agents in a single call: it fans a query out across many search engines, fuses the rankings with reciprocal rank fusion, fetches and extracts the top pages, and ranks the passages inside them. It can optionally write an answer and, with verify_quotes, check each supporting quote against its source text. A separate extract operation turns one or more URLs, including PDFs, into clean markdown or text, and the request and response shapes match Tavily so an existing Tavily client switches by changing its base URL and key.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: ASignals: 4

98%

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).

35%

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: CSignals: 4

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

32%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

93%

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: DSignals: 4

27%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

96%

OperationId Quality

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

51%

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: CSignals: 1

55%

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

77%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the Neurobird Search API to your agent

Capabilities

Start building with Neurobird Search API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

Neurobird Search API

Jentic AI Readiness Score

Neurobird Search 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