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theonlysinjin

Eos Fitting MCP Server

Pyfa MCP

MCP server that wraps the Eos EVE Online fitting engine (same stack as Pyfa). Agents propose fit changes; this server applies them, recalculates, and returns a FitReport. It never suggests modules — it only evaluates.

Install (uvx)

Once published to PyPI:

uvx pyfa-mcp

Until then, from a checkout (submodules required so Eos is bundled into the install):

git clone --recurse-submodules git@github.com:theonlysinjin/eve-fit-mcp.git
cd eve-fit-mcp
uvx --from . pyfa-mcp

Or from git directly (after submodules are fetchable in the build):

uvx --from git+https://github.com/theonlysinjin/eve-fit-mcp.git pyfa-mcp

Cursor MCP config (uvx)

{
  "mcpServers": {
    "pyfa-mcp": {
      "command": "uvx",
      "args": ["--from", "/path/to/eve-fit-mcp", "pyfa-mcp"]
    }
  }
}

After PyPI:

{
  "mcpServers": {
    "pyfa-mcp": {
      "command": "uvx",
      "args": ["pyfa-mcp"]
    }
  }
}

Staticdata downloads on first run into ~/.cache/pyfa-mcp/ (or call refresh_static_data). First Eos cache build can take a few minutes.

Requirements

  • Python 3.10+ (pulled in by uvx)

  • Network on first run for staticdata (or set EOS_PHOBOS_PATH)

  • Dev checkouts: git submodules eos, phobos, pyfa (pyfa/staticdata used when present)

Staticdata (auto / refresh)

  1. EOS_PHOBOS_PATH if set

  2. In-tree pyfa/staticdata (submodule)

  3. ~/.cache/pyfa-mcp/staticdata (or EOS_DATA_DIR)

  4. Download from GitHub release staticdata

Environment

Variable

Required

Description

EOS_PHOBOS_PATH

no

Dump root; auto-resolved if omitted

EOS_CACHE_PATH

no

Eos cache file (default under data dir)

EOS_DATA_DIR

no

Download/cache root (default ~/.cache/pyfa-mcp)

EOS_STATICDATA_URL

no

Override release asset URL

EOS_SOURCE_ALIAS

no

Default tq

EOS_PACKAGE_PATH

no

Only needed for editable/dev without wheel-bundled eos

EOS_MAX_FITS

no

Max in-memory fits (default 100)

EOS_FIT_TTL

no

Optional fit TTL in seconds

Dev install

git clone --recurse-submodules git@github.com:theonlysinjin/eve-fit-mcp.git
cd eve-fit-mcp
uv venv .venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest
pyfa-mcp   # or: python -m pyfa_mcp

Prebuilt binary

See binary-latest (pyfa-mcp-linux-x64, macOS, Windows). Point Cursor at the binary; staticdata still auto-downloads.

Creating AGENTS.md (fitting projects)

Put an AGENTS.md in the project where you design fits (not in this MCP repo):

# Fit with Pyfa MCP

You design EVE Online fits by proposing changes; the **pyfa-mcp** MCP evaluates them. It never suggests modules — you do.

Use the **eve-online-esi** MCP when the fit should reflect a real character’s skills. Prefer a cached map under `users/<Name>/skills.json`; refresh from ESI when asked or when the file is missing/stale.

## Skills (player maps)

**Apply (fitting):** load `users/<Name>/skills.json` → `set_skills(fit_id, data["skills"])`. Keys are skill type IDs; values are `active_skill_level` (0–5). Theorycraft: skip and use `apply_all_skills_5`.

**Refresh (update cache):**
1. `add_character` if needed (SSO; tokens stay local). Re-auth on 401 / missing character.
2. `GetCharactersCharacterIdSkills` with `character_id` (+ `X-Compatibility-Date`).
3. Write `users/<Name>/skills.json` as `{ character_id, name, updated_at, total_sp?, unallocated_sp?, skills: { str(skill_id): active_skill_level } }`.

## Startup

1. Confirm the goal in one line: role, constraints (EHP, DPS, tank type, cap stable?), and skills (player map via `users/…/skills.json`, or theorycraft).
2. If using a player map: load (or refresh) skills as above.
3. `create_fit(ship_type_id)` then either `set_skills` (from file) or `apply_all_skills_5`.
4. Rough in a full fit with type IDs: highs → mids → lows → rigs → drones/fighters → implants if needed.
5. Read the FitReport. Fix hard blockers first (`validation_errors`, CPU/PG/slots), then optimize toward the goal.
6. Iterate: **one** change per turn (`equip_module` / `replace_module` / `set_module_state` / `set_charge` / …). Compare reports. Use `clone_fit` for A/B forks.

## Rules

- Type IDs only — never invent them.
- Soft failures (CPU, skills, slots) still apply; hard errors (bad ID, wrong rack) do not mutate.
- Racks: `high` / `mid` / `low`. States: `offline` | `online` | `active` | `overload`.
- Stop when constraints are met or gains flatten. Summarize the final fit + key stats.

## FitReport priorities

`validation_errors` → `resources` / `slots` → `combat` (dps, ehp, RPS) → `mobility` → `fit` snapshot.

Tools (v1)

Session: create_fit, clone_fit, delete_fit, list_fits, get_fit, reset_fit
Skills: set_skills, set_skill, clear_skills, apply_all_skills_5
Hull: set_ship, set_stance, equip_module, replace_module, remove_module, set_module_state, set_charge, add_rig / remove_rig, add_subsystem / remove_subsystem, add_drone / remove_drone / set_drone_state, add_fighter / remove_fighter / set_fighter_state, add_implant / remove_implant, add_booster / remove_booster, set_effect_beacon
Eval: get_stats, validate_fit
Data: refresh_static_data

Non-goals

  • Autofitting / “make this better”

  • ESI login, skill sync, market prices

  • wx/GUI / Pyfa desktop integration

  • Full EFT/DNA import in v1

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