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How to recommend an MCP server, tool, or model to UNIGIT with Unigit Ecosystem

Submit a structured resource issue so a useful public capability can be considered.

Credentials. Never paste API keys, tokens, or other credentials into the resource issue, since the README says not to submit them.

Who it is forA developer who built or found a public MCP server, skill, template, or model and wants it considered for real user tasks.

The problemUseful public capabilities are hard to get in front of the people building AI workflows, and the submission process is unclear.

The outcomeA structured resource recommendation filed on the repo's Issues tab, with the context UNIGIT needs to evaluate it.

What you need first

  • A web browser to read the README, docs, and unigit.ai
  • A GitHub account to open Issues or Pull Requests on adtexterry-lgtm/unigit-ecosystem
  • A clear goal or resource to describe, with no credentials or customer data included

Steps

  1. Read the ecosystem guide in docs/ECOSYSTEM.md.
  2. Read the public boundary in docs/OPEN_SOURCE_SCOPE.md to confirm your resource is public and in scope.
  3. Open the Issues tab of adtexterry-lgtm/unigit-ecosystem and choose the resource issue form (template resource.yml).
  4. Describe the resource, what real work it helps with, and where it is publicly available.
  5. Remove any credentials, customer data, or unauthorized material before you submit.

Prompt for your agent

Using the adtexterry-lgtm/unigit-ecosystem README and docs/OPEN_SOURCE_SCOPE.md, draft a resource recommendation for <resource name> that follows the resource issue form. Expected output: a short draft with the resource, its public source, and the real work it supports. Verify that the draft contains no credentials, customer data, or private material.

Caveat. The README asks for public, verifiable resources only, so private or commercially sensitive tools are out of scope here.

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Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page