mcp server
agenttune
Personality tuning files for AI agents: 43 MIT-licensed tunings + 5 inline personality tests.
Description as published by the maintainer. Source
- version 1.0.0
- active
active — Most recent push to the repository was 2026-06-10.
What this server can do
3 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
get_test_spec(test)- Fetch a complete, self-contained test specification as Markdown: full item list, response scale, scoring algorithm, and the mapping from result to tuning slug. Administer the items to the user inline (bulk-paste is fine), score per the algorithm, then call get_tuning. Tests: mbti (OEJTS, 32 items, ~5 min), enneagram (OEPS, 36, ~5 min), disc (ODAT, 16, ~3 min), attachment (ECR-R, 36, ~5 min), big-five (IPIP-50, 50, ~7 min → maps to ocean files). Required: test.
get_tuning(slug, system)- Fetch one tuning file as Markdown with YAML front-matter. The front-matter is machine-readable install metadata (install.surfaces = where to write it per agent surface, verify.probe = how to confirm it took effect); the body is the behavioral tuning to load as system-prompt content. MIT licensed. Required: system, slug.
list_tunings(system)- Catalog of all 43 AgentTune personality tuning files (slug, code, name, one-line blurb), optionally filtered by system. Use it to resolve a user's personality type to the right slug before calling get_tuning.
Last successful function declaration observed on . Source: https://agent-tune.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://agent-tune.com/mcp.
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 | 2026-06-10 | 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 | 2026-06-10 | 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 | 2026-06-10 | 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 | |
| mcp tools declared | 3 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | agent-tune.com | |
| mcp endpoint status | ok | The server listed 3 functions when asked. | as of probe | agent-tune.com |
Where to get it
This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json