mcp server
io.github.caraulani/euacc-mcp
Live EU funding data in your AI: grant calls, programmes, consortium partners, VCs, incubators.
Description as published by the maintainer. Source
- version 1.0.0
- active
active — Most recent push to the repository was 2026-07-08.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 0 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-07-08 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-07-08 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-07-08 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub |
Where to get it
Related, by what their authors tagged them
-
eu.regulatoryai/sovereign-ai-act-mcp
— last commit 2026-06-15, shares europe
Classify any AI system under the EU AI Act: risk tier + binding Articles, verbatim from the law.
-
OpenPitch
— last commit 2026-07-12, shares startups
Open, sourced, confidence-scored intelligence on AI startups - a free PitchBook alternative.
-
Boletín Claro
— last commit 2026-07-29, shares grants
Subvenciones, licitaciones y boletines oficiales de España y Europa para tu IA. Gratis, sin login.
-
io.github.bch1212/mcp-grantiq
— last commit 2026-06-06, shares grants
Search US grants + federal contracts (Grants.gov + SAM.gov) from any LLM.
-
GovRider
— last commit 2026-03-12, shares grants
Match tech products and consulting services to live government tenders, grants, and RFPs
-
Canvora
— last commit 2026-07-19, shares chatgpt
Turn any idea, URL, doc, or PDF into on-brand visuals: 100+ formats, native in 150+ languages
-
DABLOCK AI Visibility Index
— last commit 2026-08-06, shares chatgpt
Measured share of answer for 24 crypto and Web3 brands. An open dataset, not an audit of your site.
-
DABYTE AI Visibility Index
— last commit 2026-08-06, shares chatgpt
Measured share of answer for 20 SaaS brands. An open dataset, not an audit of your site.
-
ai.mindola/lens
— last commit 2026-08-02, shares chatgpt
Create your digital twin: a public page that answers from your own material, with citations.
-
refd
— last commit 2026-07-30, shares chatgpt
Read AI search visibility, competitors, citations, prompts, and answer evidence from refd.
These share tags the maintainers applied themselves, such as europe, startups, grants, chatgpt. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: ai, chatgpt, claude, eu-funding, europe, grants, horizon-europe, mcp, model-context-protocol, startups.
Bring your own setup
We take apart real AI setups every week and show what broke, what cost too much, and what the trace actually said. If you run agents on real work, that is where the useful conversation is.
Join ZBS AI Practice Lab