SDKs

Available SDKs

• TypeScript SDK

• Python SDK

For AI agents (Cursor / Claude / Codex / ChatGPT / Copilot)

Don't guess operation names — read the canonical agent-facing docs first:

• Routing index + critical rules: llms.txt

• Per-operation markdown: https://api.fiber.ai/ai-docs/<operationId>.md (e.g. companySearch, syncQuickContactReveal)

• Operation index: ai-docs/index.md

• OpenAPI spec: openapi.json

• MCP server: mcp.fiber.ai/mcp/v2

TypeScript SDK

Official TypeScript/JavaScript SDK for the Fiber AI API.

Installation

npm install @fiberai/sdk
# or
yarn add @fiberai/sdk
# or
pnpm add @fiberai/sdk

Requires Node.js 18.0.0 or higher.

Authentication

All API requests require an API key. Get yours at fiber.ai/app/api.

• POST requests — pass apiKey in the request body

• GET requests — pass apiKey as a query parameter

Store your API key in an environment variable:

# .env
FIBERAI_API_KEY=your_api_key_here

Quick Start

import { companySearch } from '@fiberai/sdk';

const result = await companySearch({
  body: {
    apiKey: process.env.FIBERAI_API_KEY!,
    searchParams: {
      industriesV2: { anyOf: ['Software'] },
      // employeeCountV2 bounds are bucketed.
      // Allowed values: 0 | 1 | 10 | 50 | 200 | 500 | 1000 | 5000 | 10000 | null
      employeeCountV2: {
        lowerBoundExclusive: 50,
        upperBoundInclusive: 500,
      },
      headquartersCountryCode: { anyOf: ['USA'] },
    },
    pageSize: 10,
  },
});

console.log(`Found ${result.data?.output.data.length} companies`);
console.log('Cost:', result.data?.chargeInfo);

Examples

People Search

Find decision-makers with precise targeting by job title and country.

import { peopleSearch } from '@fiberai/sdk';

const people = await peopleSearch({
  body: {
    apiKey: process.env.FIBERAI_API_KEY!,
    searchParams: {
      jobTitleV2: {
        anyOf: [
          { type: 'term', term: 'CEO' },
          { type: 'term', term: 'CTO' },
          { type: 'static-groups', groups: ['c-suite'] },
        ],
      },
      country3LetterCode: { anyOf: ['USA'] },
    },
    pageSize: 25,
  },
});

people.data?.output.data.forEach((profile) => {
  console.log(`${profile.name} — ${profile.headline}`);
});

Contact Enrichment

Reveal work emails and phone numbers for a LinkedIn profile (sync, fast).

import { syncQuickContactReveal } from '@fiberai/sdk';

const result = await syncQuickContactReveal({
  body: {
    apiKey: process.env.FIBERAI_API_KEY!,
    linkedinUrl: 'https://www.linkedin.com/in/example',
    enrichmentType: {
      getWorkEmails: true,
      getPersonalEmails: false,
      getPhoneNumbers: true,
    },
  },
});

console.log('Emails:', result.data?.output.profile.emails);
console.log('Phones:', result.data?.output.profile.phoneNumbers);
console.log('Cost:', result.data?.chargeInfo);

For deeper coverage at higher latency or cost, use syncTurboContactEnrichment or the async waterfall triggerExhaustiveContactEnrichment + pollExhaustiveContactEnrichmentResult. For 1k+ rows, use startBatchContactEnrichment + pollBatchContactEnrichment.

Live LinkedIn Enrichment

Pull a fresh company snapshot directly from LinkedIn by slug, organization ID, or URL.

import { companyLiveEnrich } from '@fiberai/sdk';

const company = await companyLiveEnrich({
  body: {
    apiKey: process.env.FIBERAI_API_KEY!,
    type: 'slug',
    value: 'stripe',
  },
});

console.log(company.data?.output);

Check Credits

Check your organization's remaining credit balance (free — no credits charged).

import { getOrgCredits } from '@fiberai/sdk';

const credits = await getOrgCredits({
  query: { apiKey: process.env.FIBERAI_API_KEY! },
});

console.log(`Available: ${credits.data?.output.available}`);
console.log(`Used: ${credits.data?.output.used}`);

Error Handling

SDK functions return { data, error, response }. Check error before reading data:

const result = await companySearch({
  body: { apiKey: process.env.FIBERAI_API_KEY!, searchParams: { /* ... */ } },
});

if (result.error) {
  console.error(`HTTP ${result.response.status}:`, result.error);
} else {
  console.log(`${result.data.output.data.length} companies`);
}

Pass throwOnError: true to throw on non-2xx responses instead:

const result = await companySearch({
  body: { /* ... */ },
  throwOnError: true,
});
// `result.data` is now non-nullable

Common error codes:

Resources

• npm package

• GitHub repository

• API documentation

• Get an API key

• Python SDK — if you prefer Python

=====================================================================

Python SDK

Official Python SDK for the Fiber AI API.

Installation

pip install fiberai

Requires Python 3.9 or higher.

Authentication

All API requests require an API key. Get yours at fiber.ai/app/api.

The API key is passed in the request body for POST requests and as a query parameter for GET requests.

Store your API key in an environment variable:

export FIBERAI_API_KEY=your_api_key_here

Quick Start

import os
from fiberai import Client
from fiberai.api.search import company_search
from fiberai.models import CompanySearchBody
from fiberai.models.company_search_response_200 import CompanySearchResponse200

client = Client(base_url="https://api.fiber.ai")

body = CompanySearchBody.from_dict({
    "apiKey": os.environ["FIBERAI_API_KEY"],
    "searchParams": {
        "industriesV2": {"anyOf": ["Software"]},
        # employeeCountV2 bounds are bucketed.
        # Allowed: 0, 1, 10, 50, 200, 500, 1000, 5000, 10000, None
        "employeeCountV2": {
            "lowerBoundExclusive": 50,
            "upperBoundInclusive": 500,
        },
        "headquartersCountryCode": {"anyOf": ["USA"]},
    },
    "pageSize": 10,
})

result = company_search.sync(client=client, body=body)

if isinstance(result, CompanySearchResponse200):
    for company in result.output.data:
        print(company.preferred_name)
    print("Cost:", result.charge_info.to_dict())
else:
    print("error:", result.to_dict() if result else "no body")

Async Usage

Every operation has sync and async variants. Use .sync() for synchronous calls and .asyncio() for async:

import asyncio
import os
from fiberai import Client
from fiberai.api.search import company_search
from fiberai.models import CompanySearchBody

async def main():
    client = Client(base_url="https://api.fiber.ai")

    body = CompanySearchBody.from_dict({
        "apiKey": os.environ["FIBERAI_API_KEY"],
        "searchParams": {"industriesV2": {"anyOf": ["Software"]}},
        "pageSize": 10,
    })

    result = await company_search.asyncio(client=client, body=body)
    print(result)

asyncio.run(main())

Examples

People Search

Find decision-makers with precise targeting by job title and country.

from fiberai.api.search import people_search
from fiberai.models import PeopleSearchBody
from fiberai.models.people_search_response_200 import PeopleSearchResponse200

body = PeopleSearchBody.from_dict({
    "apiKey": os.environ["FIBERAI_API_KEY"],
    "searchParams": {
        "jobTitleV2": {
            "anyOf": [
                {"type": "term", "term": "CEO"},
                {"type": "term", "term": "CTO"},
                {"type": "static-groups", "groups": ["c-suite"]},
            ],
        },
        "country3LetterCode": {"anyOf": ["USA"]},
    },
    "pageSize": 25,
})

result = people_search.sync(client=client, body=body)
if isinstance(result, PeopleSearchResponse200):
    for profile in result.output.data:
        print(f"{profile.name} — {profile.headline}")

Contact Enrichment

Reveal work emails and phone numbers for a LinkedIn profile (sync, fast).

from fiberai.api.contact_details import sync_quick_contact_reveal
from fiberai.models import SyncQuickContactRevealBody

body = SyncQuickContactRevealBody.from_dict({
    "apiKey": os.environ["FIBERAI_API_KEY"],
    "linkedinUrl": "https://www.linkedin.com/in/example",
    "enrichmentType": {
        "getWorkEmails": True,
        "getPersonalEmails": False,
        "getPhoneNumbers": True,
    },
})

result = sync_quick_contact_reveal.sync(client=client, body=body)

For deeper coverage, use sync_turbo_contact_enrichment or the async waterfall trigger_exhaustive_contact_enrichment + poll_exhaustive_contact_enrichment_result. For 1k+ rows, use start_batch_contact_enrichment + poll_batch_contact_enrichment.

Live LinkedIn Enrichment

Pull a fresh company snapshot directly from LinkedIn by slug, organization ID, or URL.

from fiberai.api.live_fetch import company_live_enrich
from fiberai.models import CompanyLiveEnrichBody

body = CompanyLiveEnrichBody.from_dict({
    "apiKey": os.environ["FIBERAI_API_KEY"],
    "type": "slug",
    "value": "stripe",
})

result = company_live_enrich.sync(client=client, body=body)

Check Credits

Check your organization's remaining credit balance (free — no credits charged).

from fiberai.api.account import get_org_credits

credits = get_org_credits.sync(
    client=client,
    api_key=os.environ["FIBERAI_API_KEY"],
)

Error Handling

The non-detailed call returns a discriminated union covering every documented status. Type-narrow with isinstance to dispatch:

from fiberai.api.search import company_search
from fiberai.models.company_search_response_200 import CompanySearchResponse200
from fiberai.models.company_search_response_401 import CompanySearchResponse401
from fiberai.models.company_search_response_402 import CompanySearchResponse402
from fiberai.models.company_search_response_429 import CompanySearchResponse429

result = company_search.sync(client=client, body=body)

if isinstance(result, CompanySearchResponse200):
    companies = result.output.data
elif isinstance(result, CompanySearchResponse401):
    raise RuntimeError("invalid API key")
elif isinstance(result, CompanySearchResponse402):
    raise RuntimeError("out of credits")
elif isinstance(result, CompanySearchResponse429):
    raise RuntimeError("rate limited; back off and retry")

To raise on undocumented status codes (e.g. transient 502/503):

client = Client(
    base_url="https://api.fiber.ai",
    raise_on_unexpected_status=True,
)

Common error codes:

Available API Modules

Resources

• PyPI package

• GitHub repository

• API documentation

• Get an API key

• TypeScript SDK — if you prefer TypeScript/JavaScript