List the Gemini image-generation models available to your API key (Nano Banana / Nano Banana Pro family), and the current default model.

Resolves the credential the way real tools do, then makes one authenticated request to generativelanguage.googleapis.com. Reports which source supplied the credential, whether generativelanguage.googleapis.com accepted it, the round-trip time, and a plain-English hint distinguishing 'no credential' from 'credential rejected' from 'a generativelanguage.googleapis.com-side problem'. Call this when a real tool fails and you want to know which hop broke. Read-only; never returns the credential itself.

Generate image(s) from a text prompt with a Gemini image model (Nano Banana / Nano Banana Pro). If the result will likely be refined iteratively, prefer gemini_interact (multi-turn) as the entry point.

Edit or compose images: provide one or more input images (paths or base64), plus a text instruction. For a SERIES of successive edits to the same image, prefer gemini_interact (multi-turn) — it keeps edit context and avoids re-processing the full image each round; use gemini_image_edit for one-off edits or composing multiple distinct inputs. Gemini over-preserves the input; there is no edit-strength control — for large structural changes, reroll with a different seed or more forceful wording.

Generate a consistent SET of images: a master image from master_prompt, then one image per scene that references the master so the subject/style stays consistent. Provide scenes (explicit per-image prompts) OR count (variations of the master). Scene generations run in parallel (reference_mode "master", the default). On the hosted connector: saved characters and a saved style can seed the whole set by name, multi-image results include a bundle_url zip of every image (one curl instead of N), and max_wait_ms returns a pollable job handle if the batch runs long.

Preferred tool for iterative or multi-step refinement of a single image — multi-turn generation/editing via Gemini's Interactions API. To refine, capture the returned interaction id and pass it as previous_interaction_id on the next call — do NOT start a new interaction or re-upload the image for each tweak. continue_last: true chains from this session's most recent interaction without threading the id. If a call times out on the client side, the generation usually still completes: the image plus a <image>.json sidecar recording its interaction id land in the output dir, and continue_last: true still resumes that interaction — check the output dir before re-issuing (a re-issue is a second billable generation). If a chained call 404s, this tool re-anchors itself on the prior output image and re-issues un-chained: success is reported as chain_recovered (the chain was the problem, and you get your image anyway); a second 404 is reported as the interaction id NOT being the cause (check the model id / files uri instead). Output is JPEG.

Generate a short video via the Gemini omni model (preview): text→video, image→video / reference→video (supply reference image[s]), or edit a prior video (task: "edit" + previous_interaction_id / continue_last). Output is written to disk as MP4 (video has no inline MCP block). Video runs long — use async: true to get a job_id immediately and poll gemini_get_result, or raise timeout_ms. Preview model: needs a funded account.

Generate music from a text prompt (mood, genre, instruments, structure, or lyrics inline) via a Lyria model (preview): lyria-3-clip-preview (~30s clips, default) or lyria-3-pro-preview (longer, WAV-capable). Written to disk as MP3/WAV (or returned inline). Runs long — use async: true + gemini_get_result, or raise timeout_ms. Preview model: needs a funded account.

Retrieve a generation started with async: true or handed off by max_wait_ms. Pass the returned job_id: while running it reports status "running"; on completion it returns the normal result (image URLs/paths + meta); on failure it raises the recorded error, including the case where the generation was killed before it finished. On the hosted connector job records are stored durably and survive a restart; on a local stdio server they live with the process and expire ~10 min after completion, where the output dir / .json sidecar is the fallback. A killed video/music job started with background: true is recovered from its upstream interaction when it finished there.

Token usage for this session so far — what every generation has cost in tokens, added up. Call it before and after a workflow and subtract to get that workflow's cost; call it after a single generation for that call's. Reports tokens AND an estimated USD cost, priced per call against each call's own model and stamped with the date its rates were read (override with GEMINI_RATE_CARD). Note there is no account-balance endpoint to query — Google Cloud is post-paid and its billing data lags by hours — so this is the accurate way to attribute spend to a call.

Upload a file — an image, reference photo, picture, screenshot, video or audio clip — to the Gemini Files API ONCE, and get back a reusable file_uri (files/<id>) to attach to later image, video or music generations. Keywords: upload, upload file, upload image, upload photo, attach, reference image, reference photo, file_uri, files api, image reference, reuse across calls. Use this instead of pasting base64 into a tool call: the reference is a short string, so no image bytes ever enter the conversation, and it can be reused across many generations until it expires (~48h). Provide exactly one of url (the server downloads it), data_base64, or path (a local file).

List files, images and photos currently uploaded to the Gemini Files API under this API key, with their reusable file_uri (files/<id>) references, MIME types and expiry times. Retention is ~48h, so an entry that has vanished has expired rather than failed.

Delete an uploaded file, image or photo (by file_uri) from the Gemini Files API before its ~48h expiry. Any tool call still referencing it will then fail with a generic 404, so delete only references you are finished with.