How to connect EstimateOne to Claude Code, ChatGPT and any AI agent
Yes, Claude, ChatGPT and other AI agents can work in your EstimateOne account. EstimateOne's External API is read-only, partner-only and returns Speci-finder matches. Cotlet.dev connects your own signed-in EstimateOne account to any AI agent, so the AI finds, sorts and tracks tenders for you.
What you can ask
Find open tenders in Melbourne for electrical work closing in the next 14 days.
Which new Speci-finder matches came in this week? Rank them by project value.
Download the documents for the Westgate school tender and list the files.
Mark these 5 tenders as quoting and remind me 3 days before each closes.
Which builders invited us to quote this month?
Connect in 2 minutes
Get your API key at https://cotlet.dev/app and export it as COTLET_API_KEY.
Claude Code
claude mcp add --transport http cotlet https://cotlet.dev/mcp/v1 --header "Authorization: Bearer $COTLET_API_KEY"
ChatGPT
Settings → Apps → add connector URL https://cotlet.dev/mcp/v1, then sign in with Cotlet.dev. No API key needed.
Cursor
Copy .cursor/mcp.json from this repo into your project:
{
"mcpServers": {
"cotlet": {
"url": "https://cotlet.dev/mcp/v1",
"headers": {
"Authorization": "Bearer ${COTLET_API_KEY}"
}
}
}
}
Command line
Python 3.10+, nothing else to install. From PyPI:
pip install estimateone-mcp # or run it once: uvx estimateone-mcp connect
estimateone-mcp connect
Or straight from this repo:
export COTLET_API_KEY="your-key"
python3 estimateone_agent.py connect # ready config for Claude Code, Cursor, ChatGPT
python3 estimateone_agent.py status # is EstimateOne ready in your Cotlet.dev account
python3 estimateone_agent.py guide # EstimateOne screens and sign-in link
python3 estimateone_agent.py read # open EstimateOne, read the page, close the browser
python3 estimateone_agent.py tools # list Cotlet.dev tools
Questions from EstimateOne users
Does EstimateOne have an API?
EstimateOne has an External API for partner software: read-only, set up by EstimateOne per customer, returning Speci-finder matches. Cotlet.dev works in your own EstimateOne account, so your AI agent can do more without partner access.
Is there an EstimateOne connector for ChatGPT or Claude?
EstimateOne has no connector of its own for ChatGPT or Claude. Cotlet.dev adds one to both.
How do I connect EstimateOne to ChatGPT?
Add Cotlet.dev as an app in ChatGPT (Settings → Apps, connector URL https://cotlet.dev/mcp/v1), sign in to EstimateOne once in your Cotlet.dev Cloud Browser, and ask ChatGPT in plain words. No code and no EstimateOne API key.
Is there a way to use Claude with EstimateOne?
Yes. In Claude Code run the one-line claude mcp add command above; in the Claude app add https://cotlet.dev/mcp/v1 as a custom connector. Claude then works in your own EstimateOne account.
Also works with
Start free: https://cotlet.dev/signup?app=estimateone&utm_source=github&utm_medium=readme&utm_campaign=estimateone
Metadata
Release files for estimateone-mcp 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| estimateone_mcp-1.0.0.tar.gz | 6.1 kB | With provenance | Details for estimateone_mcp-1.0.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| estimateone_mcp-1.0.0-py3-none-any.whl | Python 3 | none | any | Details for estimateone_mcp-1.0.0-py3-none-any.whl |
Total release size: 12.5 kB
Release files / estimateone_mcp-1.0.0.tar.gz
| Download URL | estimateone_mcp-1.0.0.tar.gz |
|---|---|
| Size | 6.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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Yes |
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twine/7.0.0 CPython/3.13.16
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Signed by GitHub Actions, verified by PyPI on Nov 7, 2026.
Transparency logRelease files / estimateone_mcp-1.0.0-py3-none-any.whl
| Download URL | estimateone_mcp-1.0.0-py3-none-any.whl |
|---|---|
| Size | 6.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
61faeeec654bd470d8ee99e1037f2d48e464253836f26a91693bbbd4a89d4d09
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84d5a80a288b96a67e7f0ee88673f968ef211478f2db9101eabbf6c61615df67
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
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PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 7, 2026.
Transparency logSecurity for estimateone-mcp 1.0.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
Both files in this release have been uploaded with provenance metadata.
Attestation for estimateone_mcp-1.0.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 7, 2026.
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