AI 에이전트가 스스로 할 수 없는 한 가지를 제공하세요: 실제로 코드를 테스트에 대해 실행하고 통과했음을 증명하는 것.
Soma는 실행 검증 코드 서비스입니다. 이 MCP 서버는 두 가지 도구를 제공합니다:
soma_verify_code — 격리된 샌드박스에서 테스트에 대해 후보 코드를 실행하고 PASS/FAIL 판정과 서명된 오프라인 검증 가능 인증서(Ed25519)를 받으세요. 코드를 신뢰하기 전에 독립적으로 작동을 확인하는 데 사용하세요.
soma_generate_verified_code — Soma에 작업에 대한 코드 작성을 요청하세요. 작업이 검증 가능한 경우, 반환된 코드는 파생된 테스트에 대해 이미 실행되었으며 인증서가 첨부되어 있습니다.
검증을 위해 15개 이상의 언어가 지원됩니다 (Python, JavaScript/TypeScript, Go, C/C++, Java, Rust, Ruby, PHP, Bash 등).
Node.js 18+ 필요. stdio로 실행됩니다.
MCP 클라이언트 구성(Claude Desktop, Cursor 등)에 추가하세요:
{
"mcpServers": {
"soma": {
"command": "npx",
"args": ["-y", "soma-verify-mcp"],
"env": {
"SOMA_API_KEY": "YOUR_SOMA_KEY"
}
}
}
}Claude Desktop: Settings → Developer → Edit Config에서 위 블록을 추가하고 재시작하세요.
Cursor: Settings → MCP → Add에서 추가하거나 ~/.cursor/mcp.json에 동일한 블록을 넣으세요.
Related MCP server: OmniBridge MCP Server
환경 변수 | 필수 | 기본값 | 용도 |
| 예 | — | Soma API 키. |
| 아니요 |
| Soma API 기본 URL. |
| 아니요 |
| 요청당 제한 시간. |
무료 미리보기 키 받기: centrum.arvind@gmail.com 문의 (미리보기 기간 동안 무료 티어).
soma_verify_code테스트에 대해 코드를 실행하고 서명된 판정을 반환합니다.
language (string) — 예: python, javascript, go, rust.
code (string) — 검증할 전체 소스 코드.
tests (array) — 다음 중 하나:
함수 모드 (기본값): [{ "input": [arg1, arg2], "expected": value }] 및 entrypoint (함수 이름).
stdio 모드: mode: "stdio" 및 [{ "stdin": "...", "expected_stdout": "..." }] 설정; entrypoint 없음.
entrypoint (string, 선택 사항) — 함수 모드의 함수 이름.
mode ("function" | "stdio", 선택 사항).
반환: verdict, tests_passed, tests_total, 그리고 오프라인에서 확인할 수 있는 signature / public_key / sig_alg.
soma_generate_verified_code작업에 대한 코드를 받고, 반환되기 전에 파생된 테스트에 대해 실행됩니다.
prompt (string) — 코딩 작업. 구체적인 입력/출력 예시를 포함하세요 (예: >>> f(2) == 4) 그래야 결과가 최선 노력이 아닌 검증 가능합니다.
max_tokens (int, 선택 사항, 기본값 1500).
반환: 코드, certified (bool), 그리고 검증이 통과된 경우 certificate (verdict, tests_passed, tests_total). 작업이 검증 가능하지 않은 경우, 출력은 인증되지 않은 상태로 명확히 표시되어 반환됩니다 — 결코 거짓 "verified"가 아닙니다.
인증서는 나열된 테스트가 생성 시점에 격리된 샌드박스 내에서 통과했음을 증명합니다. 서명(Ed25519)되어 있으며 반환된 공개 키로 오프라인에서 확인할 수 있습니다. 어떤 목적에 대한 적합성 보증은 아닙니다 — 프로덕션 사용 전에 출력을 검토하세요.
프롬프트에 대한 학습이 없습니다. ${SOMA_BASE_URL}/privacy에서 Soma 개인정보 보호 및 데이터 정책을 확인하세요.
MIT.
Ask Soma to write code for a task. When the task is verifiable, the returned code has been executed against derived tests in an isolated sandbox before it is returned, and a certificate (verdict + tests passed) is attached. Include concrete examples in the prompt (e.g. doctest-style '>>> f(2) == 4') to make the result verifiable rather than best-effort.
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The coding task. Include example input/output pairs to enable verification. | |
| max_tokens | No | Maximum output tokens (default 1500). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe, non-destructive operation. The description adds valuable behavioral context: the code is executed in an isolated sandbox, a certificate with verdict and tests passed is attached, and the verification is conditional on task verifiability. This goes beyond the annotations and provides important expectations about the output and process.
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?
The description is concise and well-structured. It front-loads the core purpose, then explains the verification process and provides actionable advice on prompt construction. Every sentence adds value, and there is no fluff or repetition. The structure is logical: what it does, how it works, and how to use it effectively.
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 the tool's complexity (verification, sandbox, certificate) and the absence of an output schema, the description covers the essential aspects: what the tool does, how verification works, and how to improve results. It does not detail the certificate format or the exact conditions for verifiability, but these are not critical for an agent to invoke the tool correctly. The description is complete enough for effective use.
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 description coverage is 100%, so both parameters (prompt and max_tokens) are already documented in the schema. The description adds guidance on how to use the prompt parameter (include concrete examples) and mentions the default for max_tokens, but this is largely redundant with the schema. The description does not add significant new meaning beyond the schema, so a baseline 3 is appropriate.
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 tool's purpose: 'Ask Soma to write code for a task.' It specifies the key differentiator—execution-verified code with a certificate—and distinguishes it from a best-effort generation. The verb 'write code' and resource 'task' are specific, and the mention of verification sets it apart from the sibling tool.
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 provides clear guidance on when to use this tool: when the task is verifiable, and it advises including concrete examples in the prompt to enable verification. It implies that for non-verifiable tasks, this tool may not be ideal, but it does not explicitly name the sibling tool or state when to use soma_verify_code instead. The guidance is strong but lacks an explicit exclusion or alternative mention.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run candidate code against tests inside an isolated sandbox and return a PASS/FAIL verdict with a signed, offline-checkable certificate (Ed25519). Use this to independently confirm that code actually works before trusting it.
Two test shapes:
function mode (default): tests = [{"input": [arg1, arg2], "expected": value}] and provide 'entrypoint' (the function name).
stdio mode: set mode='stdio' and tests = [{"stdin": "...", "expected_stdout": "..."}]; no entrypoint needed.
Supported languages include python, javascript, typescript, go, c, cpp, java, rust, ruby, php, bash and more.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | The complete source code to verify. | |
| mode | No | 'function' (default) or 'stdio'. | |
| tests | Yes | function mode: [{input:[args], expected: value}]. stdio mode: [{stdin:'...', expected_stdout:'...'}]. | |
| language | Yes | Programming language, e.g. 'python', 'javascript', 'go', 'rust'. | |
| entrypoint | No | Function name to call (required for function mode; omit for stdio mode). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description reveals the isolated sandbox behavior and the signed certificate output, adding value beyond the annotations. It does not specify sandbox limits, timeouts, or what happens on ambiguous test results, but the key isolation and non-destructive nature are explicit.
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?
Well-organized with clear separation of modes, languages, and purpose. Slightly verbose but every line adds value. Could be tightened, but readability is strong.
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?
Covers when to use (independent confirmation), the two modes, supported languages, and the output certificate nature. Missing: no example usage, no details on error handling or timeouts, and output format isn't specified, but the description is otherwise informative enough for an agent to call it correctly.
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?
The schema documents all five parameters with types and required status, and the description adds concrete examples for tests structures in both modes. Entry point requirement is clarified. Coverage is 100% and the semantics are unambiguous.
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 tool verifies code against tests in a sandbox and returns a signed certificateat. Uses specific verbs (verify, return PASS/FAIL) and names two precise modes. Though siblings weren't supplied for comparison, it self-defines scope well.
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 clear usage context: 'Use this to independently confirm that code actually works before trusting it.' Describes two modes (function and stdio) with examples. Does not explicitly list when-not-to-use or alternatives, but the context is enough for most agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0soma_generate_verified_codesoma_verify_codeScored across 2 tools
The two tools have clearly distinct purposes: one verifies provided code, the other generates code with verification. There is no overlap or confusion between them.
Both tools follow the identical pattern of 'soma_' prefix plus a verb_noun structure: verify_code and generate_verified_code. Naming is uniform and predictable.
With only 2 tools, the server is minimal but focused on a narrow purpose. While the count feels thin for a general toolkit, it is reasonable for a specialized verification service. It sits at the borderline.
The server covers the core workflows of code verification and generation with verification. Minor gaps exist, such as no ability to fetch or check certificate details after generation, but the primary lifecycle is covered.
Hosted Python sandbox for package runtime verification: pip install and usable-import evidence.
Execute code in 8 languages (Python, JS, TS, Go, Java, C++, C, Bash) in gVisor sandboxes.
Signed sandbox verdicts on any artifact, plus an agent marketplace. No key, no signup, no payment.
Attestation infrastructure for the agentic economy: signed, independently verifiable verdicts.
