MangoBoost website screenshot

MangoBoost

MangoBoost, Inc. builds full-stack Data Processing Unit (DPU) hardware and AI-infrastructure software for data centers. Founded in 2022 and headquartered in Seattle with operations in Canada and Korea, the company ships the Mango BoostX DPU family (RoCE AI / RDMA, NVMe-oF initiator and target, TCP Offload Engine), the Mango SDK — a C/C++ device library (libmango), CLI tools (mango-ctl, mango-smi) and an OPI-compliant gRPC storage bridge — and Mango LLMBoost, an enterprise LLM inference server that exposes a drop-in OpenAI-compatible REST API on customer-owned AMD Instinct GPUs. Its developer surface is self-hosted rather than SaaS: the LLMBoost server is distributed as a container plus the llmboost_hub (lbh) Python CLI, and the DPU is programmed through libmango and OPI gRPC on the card.

MangoBoost publishes 3 APIs on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine-Learning, Infrastructure, and Data-Center.

MangoBoost’s developer surface includes CLI, authentication, documentation, API reference, getting-started guide, support, engineering blog, and 21 more developer resources.

29.8/100 thin ▬ flat Agent 5/100 agent aware open core · Apache-2.0 Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0
AccessOpen
3 APIs
CompanyArtificial IntelligenceMachine-LearningInfrastructureData-CenterSemiconductorsHardwareStorageNetworkingInferenceGPUDPU

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0
Open Source Surface applies to this provider. This product is open source and we read its repository directly, so Open Source Surface carries 10 points of the composite. It is scored from what the repository actually publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the provider rather than inferred from our own catalog pointers. This facet adds; nothing was taken away to make room for it. An open-source project is not excused from the commercial facets, because exemption would strip it of the points it does earn. If we have the wrong repository, or this product is not open source, say so on your provider repo and we will drop the facet rather than have you publish against it.
Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.
The six quality facets above are damped to 90 points between them, because the conditional facet above carries the other 10. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 90% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from github.com/api-evangelist/mangoboost: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

APIs 3

Individual APIs this provider publishes, each with its own machine-readable definition.

Mango LLMBoost Inference Server API

LLMBoost is MangoBoost's enterprise LLM inference server. It serves the OpenAI REST API on /v1 so an existing OpenAI client migrates with a base-URL change: POST /v1/chat/comple...

Mango SDK Device API (libmango)

The Mango SDK development package (libmango-dev) provides the C/C++ user API, libraries and example applications for programming MangoBoost DPU devices. Documented API groups ar...

Mango OPI Storage Bridge gRPC API

MangoBoost ships an Open Programmable Infrastructure (OPI) gRPC bridge that translates standard OPI storage API calls into MangoBoost SDK / SPDK RPC calls on the DPU, so NVMe-oF...

Security Posture 2

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Mangoboost Authentication

0 schemes

SECURITY

Resources

Get Started 2

Portal, sign-up, and the first successful call

Documentation 2

Reference material describing how the API behaves

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 4

Pagination, idempotency, versioning, errors, and events

Build 4

SDKs, sample code, and the tooling you integrate with

Access & Security 2

Authentication, authorization, and security posture

Operate 3

Status, limits, changes, and where to get help

Commercial 3

Pricing, plans, and the legal terms of use

Company 6

The organization behind the API

Other 1

Properties that don't map to a standard resource type

Source (apis.yml)

apis.yml Raw ↑
aid: mangoboost
name: MangoBoost
description: 'MangoBoost, Inc. builds full-stack Data Processing Unit (DPU) hardware and AI-infrastructure software for data
  centers. Founded in 2022 and headquartered in Seattle with operations in Canada and Korea, the company ships the Mango BoostX
  DPU family (RoCE AI / RDMA, NVMe-oF initiator and target, TCP Offload Engine), the Mango SDK — a C/C++ device library (libmango),
  CLI tools (mango-ctl, mango-smi) and an OPI-compliant gRPC storage bridge — and Mango LLMBoost, an enterprise LLM inference
  server that exposes a drop-in OpenAI-compatible REST API on customer-owned AMD Instinct GPUs. Its developer surface is self-hosted
  rather than SaaS: the LLMBoost server is distributed as a container plus the llmboost_hub (lbh) Python CLI, and the DPU
  is programmed through libmango and OPI gRPC on the card.'
url: https://raw.githubusercontent.com/api-evangelist/mangoboost/refs/heads/main/apis.yml
deliveryModel:
  model: open-core
  license: Apache-2.0
  open_source: true
  commercial: true
  callable_host: false
  label: Open core · an OSS project plus a commercial hosted product
  confidence: high
  source:
  - license
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: open
  trial: false
  try_now: false
  public: false
  label: Open access
  confidence: low
  try_now_blocked_by: loopback
  source:
  - authentication
  - security
  generated: '2026-09-02'
  method: derived
image: https://cdn.sanity.io/images/hx87iaks/production/044e3e87d4c32dc3c01996e772f4b3f7c08b873e-376x61.png
x-type: company
x-source: harvest:secondary-market
x-harvest-url: https://forgeglobal.com/mangoboost_stock/
x-tier: profiled
x-tier-reason: enrichment
specificationVersion: '0.23'
created: '2026-08-04'
modified: '2026-08-04'
tags:
- Company
- Artificial Intelligence
- Machine-Learning
- Infrastructure
- Data-Center
- Semiconductors
- Hardware
- Storage
- Networking
- Inference
- GPU
- DPU
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Infrastructure
- Data Center
- Semiconductors
- Hardware
- Storage
- Networking
- Inference
- GPU
- DPU
apis:
- aid: mangoboost:llmboost-inference
  name: Mango LLMBoost Inference Server API
  description: 'LLMBoost is MangoBoost''s enterprise LLM inference server. It serves the OpenAI REST API on /v1 so an existing
    OpenAI client migrates with a base-URL change: POST /v1/chat/completions, POST /v1/completions, POST /v1/embeddings, POST
    /v1/responses, POST /v1/audio/transcriptions and /translations, GET /v1/models, plus GET /health and GET /metrics (Prometheus).
    Streaming, JSON-schema structured output, tool/function calling and multimodal image input are supported. The server is
    self-hosted on the customer''s own AMD Instinct GPUs — there is no MangoBoost-hosted endpoint — and is started with `lbh
    serve <Repo/Model>` or `llmboost serve <model>` inside the LLMBoost container.'
  humanURL: https://llmboost.mangoboost.io/docs/features/openai-api
  baseURL: http://localhost:8000/v1
  x-deployment: self-hosted
  x-default-port: 8000
  tags:
  - Inference
  - Artificial Intelligence
  - LLM
  - OpenAI-Compatible
  - Self-Hosted
  tags_raw:
  - Inference
  - Artificial Intelligence
  - LLM
  - OpenAI Compatible
  - Self Hosted
  properties:
  - type: Documentation
    url: https://llmboost.mangoboost.io/docs/
  - type: GettingStarted
    url: https://llmboost.mangoboost.io/docs/quickstart
  - type: APIReference
    url: https://llmboost.mangoboost.io/docs/features/openai-api
- aid: mangoboost:mango-sdk
  name: Mango SDK Device API (libmango)
  description: The Mango SDK development package (libmango-dev) provides the C/C++ user API, libraries and example applications
    for programming MangoBoost DPU devices. Documented API groups are Common, Device Context, Memory, DMA Transfer, TCP/IP
    Offload, TLS Offload, POSIX (compatibility shims), AI Image Preprocess, GPU StorageBoost (GSB), RDMA PCC and Software-Defined
    Device. Applications include libmango.h and link with pkg-config; packages are distributed as .deb/.rpm (mango-sdk, mango-cli,
    libmango-dev, mango-drivers, mango-drivers-spdk) obtained by contacting MangoBoost.
  humanURL: https://sdk.mangoboost.io/docs/api/
  x-deployment: on-device-library
  tags:
  - SDK
  - DPU
  - Storage
  - Networking
  - RDMA
  properties:
  - type: Documentation
    url: https://sdk.mangoboost.io/docs/guide/
  - type: APIReference
    url: https://sdk.mangoboost.io/docs/api/
- aid: mangoboost:opi-storage-bridge
  name: Mango OPI Storage Bridge gRPC API
  description: MangoBoost ships an Open Programmable Infrastructure (OPI) gRPC bridge that translates standard OPI storage
    API calls into MangoBoost SDK / SPDK RPC calls on the DPU, so NVMe-oF initiator (NTI) and target (NTT) offloads can be
    configured with the vendor-neutral OPI interface. The bridge listens on gRPC port 50051 with an HTTP gateway on 8082;
    documented calls include CreateNvmeSubsystem, CreateNvmeController, CreateNvmeRemoteController, CreateNvmePath and CreateNvmeNamespace.
    The implementation is open source under the Linux Foundation OPI project as opi-mangoboost-bridge.
  humanURL: https://sdk.mangoboost.io/docs/guide/docs_opi/overview
  x-deployment: on-device-grpc
  x-default-port: 50051
  tags:
  - gRPC
  - Storage
  - NVMe-oF
  - OPI
  - DPU
  properties:
  - type: Documentation
    url: https://sdk.mangoboost.io/docs/guide/docs_opi/guide
  - type: SourceCode
    url: https://github.com/opiproject/opi-mangoboost-bridge
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: IssueTracker
  url: https://github.com/opiproject/opi-mangoboost-bridge/issues
- type: Releases
  url: https://github.com/opiproject/opi-mangoboost-bridge/releases
- type: License
  name: Apache-2.0
  url: https://github.com/opiproject/opi-mangoboost-bridge/blob/main/LICENSE
- type: DomainSecurity
  url: security/mangoboost-domain-security.yml
- type: Packages
  url: packages/mangoboost-packages.yml
- type: SDKs
  url: packages/mangoboost-packages.yml
- type: CLI
  url: cli/mangoboost-cli.yml
- type: Authentication
  url: authentication/mangoboost-authentication.yml
- type: Conventions
  url: conventions/mangoboost-conventions.yml
- type: ErrorCatalog
  url: errors/mangoboost-error-codes.yml
- type: Lifecycle
  url: lifecycle/mangoboost-lifecycle.yml
- type: Conformance
  url: conformance/mangoboost-conformance.yml
- type: LLMsTxt
  url: llms/mangoboost-llms.txt
- type: Website
  url: https://www.mangoboost.io/
- type: DeveloperPortal
  url: https://sdk.mangoboost.io/
- type: Documentation
  url: https://llmboost.mangoboost.io/docs/
- type: APIReference
  url: https://sdk.mangoboost.io/docs/api/
- type: GettingStarted
  url: https://llmboost.mangoboost.io/docs/quickstart
- type: Support
  url: https://www.mangoboost.io/contact
- type: Blog
  url: https://www.mangoboost.io/resources/blog
- type: GitHubOrganization
  url: https://github.com/MangoBoost
- type: TermsOfService
  url: https://www.mangoboost.io/terms-of-service
- type: PrivacyPolicy
  url: https://www.mangoboost.io/privacy-policy
- type: Careers
  url: https://www.mangoboost.io/careers
- type: News
  url: https://www.mangoboost.io/media/news
- type: Publications
  url: https://www.mangoboost.io/resources/publications
- type: LinkedIn
  url: https://www.linkedin.com/company/mangoboost/
- type: Twitter
  url: https://x.com/mangoboost_inc
x-enrichment:
  date: '2026-08-04'
  status: enriched
  artifacts_added: 10
  pass: local-v1
x-coverage:
  state: covered
  reason: no-machine-readable-spec
  detail: Fully profiled from three live, server-rendered documentation hosts, but MangoBoost publishes no machine-readable
    contract for any of its three API surfaces — /openapi.json, /openapi.yaml, /swagger.json, /api-docs and /redoc all return
    404 on www., sdk. and llmboost.mangoboost.io, and the OPI gRPC bridge ships no first-party .proto. The LLMBoost server
    is OpenAI-compatible, so an OpenAPI describing its /v1 surface would be cheap for them to publish.
  evidence:
  - url: https://llmboost.mangoboost.io/docs/features/openai-api
    status: 200
  - url: https://sdk.mangoboost.io/docs/api/
    status: 200
  - url: https://llmboost.mangoboost.io/openapi.json
    status: 404
  - url: https://www.mangoboost.io/llms.txt
    status: 404
  checked: '2026-08-04'

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