tunova
Server Details
Generate Suno AI music (v5.5) from any MCP client. Async; billed only on success.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- erliona/tunova-sdk
- GitHub Stars
- 0
- Server Listing
- Tunova
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Tool Definition Quality
Average 4.4/5 across 3 of 3 tools scored.
Each tool has a distinct role: starting generation, single status check, and polling until completion. No overlap or ambiguity.
All tool names follow the verb_noun pattern with underscores (e.g., generate_song), consistent across the set.
Three tools cover the core workflow of generating a song with Suno: initiate, check status, and wait. Perfectly scoped.
The tool surface covers the full lifecycle of song generation: create, status check, and retrieval. No obvious missing operations.
Available Tools
3 toolscheck_songAInspect
Get the current status of a song job by job_id — a single check with no waiting. Returns the audio URLs if complete, an error if it failed, or 'processing' if still rendering.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | The job_id returned by generate_song. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description fully discloses behavior: returns three states (complete URLs, error, processing) and non-blocking nature ('no waiting'). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with purpose, efficient, and contains no extraneous information. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description completely covers return types (audio URLs, error, processing) and input origin. No gaps for a simple poll tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage for job_id. Description adds context that job_id comes from generate_song, reinforcing the tool's dependency and usage pattern.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get the current status' and resource 'song job by job_id'. Distinguishes from siblings by noting 'single check with no waiting', contrasting with wait_for_song.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for one-time checks without polling via 'no waiting', but does not explicitly state when to use vs alternatives or provide exclusions. Sibling tools are named but no direct comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_songAInspect
Start generating a song with Suno. Returns immediately with a job_id — a full render takes 1-3 minutes, so this does NOT return audio. After calling this, call wait_for_song with the returned job_id to get the audio URL when ready. Costs 10 tokens, billed only on success.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | Style/genre, e.g. 'lofi hip hop, mellow, rainy'. Most useful in custom mode. | |
| model | No | Suno model version (v5.5 — the only model). Optional; defaults to v5.5. | |
| title | No | Song title (custom mode). | |
| custom | No | false (default): describe the song and Suno writes everything. true: `prompt` is the literal lyrics, and `tags`/`title` are used. | |
| prompt | Yes | What the song should be about (simple mode), or the exact lyrics (when custom=true). | |
| instrumental | No | If true, generate without vocals. | |
| idempotency_key | No | Optional logical-request id. Reuse it to recover one submit; use a new value to intentionally generate the same song again or retry after a terminal failed job. When omitted, Tunova derives a stable key from the song arguments for safe automatic retries. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors: asynchronous (1-3 min render), immediate return, cost of 10 tokens billed only on success. No annotations, but description covers core traits. Could mention rate limits or failure modes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, async behavior and next step, cost. No fluff, front-loaded with key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains output (job_id) and sequencing with wait_for_song. Lacks output schema but description covers return type. Could address error handling, but sufficient for the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 7 parameters with descriptions (100% coverage). Description adds no new parameter-level info beyond referring to job_id return. Baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool initiates song generation with Suno, returns job_id immediately, and explicitly distinguishes from siblings by directing to call wait_for_song for audio. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit usage flow: call this, then wait_for_song. Mentions billing on success. Does not explicitly state when not to use or alternatives, but the sequence is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
wait_for_songAInspect
Wait for a song job to finish and return the audio when ready. Polls server-side for up to ~45 seconds. If the song is ready, returns the clips with audio URLs. If it is still rendering, returns its status so you can call wait_for_song again with the same job_id. Safe to call repeatedly — it only reads status, never starts a new song.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | The job_id returned by generate_song. | |
| max_wait_seconds | No | How long to wait before returning (default 45, max 55). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses polling, max wait time, return behavior (clips with URLs or status), and safety (read-only, no new song creation). This is sufficient for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each adding distinct information: purpose, polling time, outcomes, safety. No unnecessary words, well front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description explains returns (clips with audio URLs or status). Could be more precise about status structure, but adequate for a polling tool with 2 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds context beyond schema: explains job_id is from generate_song and max_wait_seconds default/max. Also clarifies polling behavior and that it returns status for retries, adding meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'wait for' and the resource 'song job'. It distinguishes itself from sibling tools by emphasizing it only reads status and never starts a new song, contrasting with generate_song.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that it should be used after generate_song, can be called repeatedly if not ready, and is safe. It implicitly suggests using this for polling but does not explicitly mention when to use check_song instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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