mcp-nexus
MCP Nexus
MCP Nexus — это локально-ориентированный интеллектуальный маршрутизатор для Model Context Protocol. Ваша ИИ-среда подключается к одной конечной точке MCP — Nexus, — в то время как Nexus управляет всеми вашими реальными MCP-серверами за кулисами: индексирует их инструменты, обнаруживает возможности по запросу, запускает серверы лениво, выполняет маршрутизированные вызовы и учится на локальном использовании, чтобы со временем лучше ранжировать результаты.
Before With MCP Nexus
AI Harness AI Harness
├── GitHub MCP (30 tools) └── mcp-nexus (4 control tools)
├── Jira MCP (25 tools) ├── search_capabilities
├── Slack MCP (20 tools) ├──── describe_capabilities
├── Figma MCP (18 tools) ├──── execute_capability
... └──── search_servers
~90+ tool schemas in context │
(everything else stays indexed
on disk until actually needed)Зачем
Каждый подключенный MCP-сервер добавляет схемы инструментов в контекст модели. Через десять серверов вы сжигаете десятки тысяч токенов на определения, которые модель редко использует, и качество выбора инструментов ухудшается.
Nexus переворачивает модель: вместо того чтобы помещать каждую нижестоящую схему в контекст, он хранит легковесный индекс возможностей на диске и предоставляет крошечную плоскость управления. Агент обнаруживает возможности по мере необходимости (search_capabilities), просматривает точные схемы только для выбранного (describe_capabilities) и выполняет через Nexus (execute_capability). Все состояние — конфигурация, индекс, аналитика, изученные последовательности — хранится локально в .mcp-nexus/.
Related MCP server: MCP Server Proxy
Быстрый старт
# 1. Scaffold a project config
npx @fyrlabs/mcp-nexus init
# 2. Add downstream MCP servers (anything runnable over stdio)
npx @fyrlabs/mcp-nexus add github -- npx -y @modelcontextprotocol/server-github
# or import an existing config:
npx @fyrlabs/mcp-nexus import --from claude
# 3. Point your harness at Nexus (see docs/harness-setup.md)Конфигурация среды (Claude Code, Cursor, Codex и другие MCP-клиенты):
{
"mcpServers": {
"mcp-nexus": {
"command": "npx",
"args": ["-y", "@fyrlabs/mcp-nexus"]
}
}
}Nexus автоматически находит project-mcp.json, поднимаясь от рабочего каталога, или передайте --config ./path/to/nexus.json.
Затем, с точки зрения агента:
search_capabilities { "query": "find comments people left on my PR" }
→ github.review_comments.list score=0.94 ...
describe_capabilities { "capabilityIds": ["github.review_comments.list"] }
→ exact input schema
execute_capability { "capabilityId": "github.review_comments.list",
"arguments": { ... } }
→ forwarded verbatim to the right server, started on demandЧто раскрывается, а что остается скрытым
Раскрывается модели | Остается локальным | |
Инструменты плоскости управления | 4 фиксированных инструмента | — |
Метаданные возможностей | Только при поиске (небольшие записи: id, название, описание, риск, оценка) | Полный индекс в SQLite |
Схемы входных данных инструментов | Только для описанных возможностей | Сохраняются при индексации |
Аналитика использования | — | Локальные события + агрегаты |
Секреты | Никогда (ссылки на env разрешаются при запуске, скрыты из логов) | В вашей оболочке/окружении |
Основные возможности
Локально-ориентированный. Никакого облачного сервиса, аккаунта или телеметрии. Удалите
.mcp-nexus/— и все изученное состояние исчезнет.Ленивый жизненный цикл. Нижестоящие серверы запускаются только когда задача требует их, и останавливаются после многоуровневых тайм-аутов простоя (горячий / теплый / холодный).
Гибридный поиск. Лексическое ранжирование BM25 по взвешенным полям, точное совпадение id/инструмента, расширение алиасов (
pr → pull request, настраивается) и подключаемый интерфейсEmbeddingProviderдля опциональных семантических слоев.Адаптивное ранжирование с пояснениями. Каждый результат содержит разбивку сигналов; закрепленные возможности превосходят изученную популярность; заблокированные возможности никогда не предлагаются.
Предсказание последовательностей. Повторяющиеся переходы инструментов изучаются локально и используются для повышения вероятных следующих возможностей — предсказание никогда не выполняется автоматически.
Ноль нативных зависимостей. Хранилище использует встроенный
node:sqliteиз Node; установка этого пакета ничего не компилирует.Независимость от среды. Все, что говорит на MCP stdio, может стоять перед Nexus.
Требования
Node.js >= 22.5 (рекомендуется 24 LTS)
Документация
Справочник по конфигурации — каждое поле, порядок разрешения, подстановка env
Справочник по CLI — все команды и флаги
Архитектура — модули, модель оценки, схема хранилища
Настройка среды — Claude Code, Cursor, Codex, универсальные MCP-клиенты
examples/project-mcp.json— аннотированный стартовый конфиг
Разработка
git clone https://github.com/fyrlabs/mcp-nexus && cd mcp-nexus
npm install
npm run build # tsc -> dist/
npm run test # vitest (unit + integration, mirrors src/ structure under src/tests/)
npm run typecheck # strict tsc, no emit
npm run lint # eslintИнтеграционные тесты запускают реальный пакет @modelcontextprotocol/server-everything в качестве нижестоящего stdio-сервера и маршрутизируют выполнение через полный рантайм — они автоматически пропускаются, если пакет не может быть разрешен.
Смотрите AGENTS.md для соглашений о вкладе (коммиты, версионирование, структура).
Конфиденциальность
Nexus хранит кэши конфигурации, индексы и аналитику в .mcp-nexus/ (или в вашей XDG-директории данных). Сам маршрутизатор ничего никуда не отправляет. Если вы настроите внешнего провайдера эмбеддингов, туда будут отправляться только тексты возможностей (названия/описания/ключевые слова) — никогда аргументы, секреты или аналитика. Сырые аргументы инструментов никогда не сохраняются.
Лицензия
Available Tools
4 toolsdescribe_capabilitiesDescribe capabilitiesB
Return the full metadata and input schemas for the given capability IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| capabilityIds | Yes | Capability IDs returned by search_capabilities |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It clearly states the tool returns metadata and schemas, which is a read-like operation, but it doesn't disclose any limitations, such as whether invalid IDs cause errors or whether the returned data is verbose. The description is accurate but sparse on behavioral nuances.
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?
A single clear sentence that is entirely on-topic. It front-loads the action and object, with no filler. Could earn a 5 if it referenced a sibling or workflow, but it remains efficient.
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 there is no output schema and no annotations, the description is the sole source of behavioral information. It tells the agent what the tool returns, but for a metadata-inspection tool, an agent might need to know whether it can be used before executing a capability or how errors are surfaced. Still, for a simple lookup tool, this is adequate.
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%, so the schema already documents the 'capabilityIds' parameter. The description adds the purpose context ('full metadata and input schemas') but doesn't add format or constraint details beyond the schema. Baseline 3 applies.
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?
States a specific verb ('Return') and resource ('metadata and input schemas') for given capability IDs. It distinguishes itself from sibling tools like search_capabilities (which likely finds capabilities) and execute_capability (which runs them), though it doesn't explicitly name them.
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 implies usage: given capability IDs, retrieve metadata. The parameter description notes IDs come from search_capabilities, implicitly showing a workflow step. However, it doesn't state when to use this vs execute_capability or search_servers, leaving some inference needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
execute_capabilityExecute capabilityA
Execute a downstream MCP capability by ID. The underlying server is started on demand and the arguments are forwarded verbatim.
| Name | Required | Description | Default |
|---|---|---|---|
| arguments | No | Arguments matching the tool's input schema (see describe_capabilities) | |
| capabilityId | Yes | Capability ID to execute |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses two genuine behaviors: the backing server is 'started on demand' (affecting latency/resource use) and arguments are 'forwarded verbatim' (no transformation). It does not mention output shape, error behavior, or potential side effects of the downstream capability, so coverage is partial.
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?
Two sentences, each adding distinct information: the core action and two behavioral caveats. No redundant or filler wording, and the most important information is 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?
The definition is largely sufficient for a simple pass-through invocation, and the arguments schema points to describe_capabilities for the input contract. However, there is no output schema or description of the return value/error behavior, so an agent does not know what to expect after invocation. This is a moderate gap given no annotations.
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 already documents both parameters completely (100% coverage), so the baseline is 3. The description's 'arguments are forwarded verbatim' reinforces the arguments parameter's semantics, but adds no new parameter-specific detail beyond the schema, which already tells the agent to see describe_capabilities for the expected argument shape.
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?
States a specific action – 'Execute a downstream MCP capability by ID' – with a clear verb and resource. The 'by ID' scoping and the 'downstream MCP' qualifier distinguish it from siblings like describe_capabilities and search_capabilities, which are informational rather than invocational.
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 implies usage: you invoke this when you have a capability ID and want to run it, and the 'forwarded verbatim' phrasing indicates arguments should already conform to the target schema. It does not explicitly list exclusions or alternatives, but the sibling names make the distinction clear. This is adequate context without explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_capabilitiesSearch capabilitiesA
Search every indexed downstream MCP capability by natural language, keywords, tags, server id, or capability id. Returns lightweight metadata only.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return | |
| query | Yes | Natural language or keyword query describing the capability you need |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full behavioral burden. It usefully discloses that the tool is a search operation returning 'lightweight metadata only', which implies read-only behavior and no full payload or execution. However, it does not mention result shape, pagination behavior, indexing caveats, or what happens when nothing matches.
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?
One dense, front-loaded sentence carries the purpose, scope, search dimensions, and return nature with no filler. Every phrase earns its place, and the most important information appears first.
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?
For a simple two-parameter search tool, the description is largely complete: the query semantics are enriched, the limit is documented in the schema, and the return type is characterized. The main remaining gap is the absence of an output schema or a more concrete list of returned metadata fields, but this does not prevent a capable agent from selecting and invoking the tool 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?
Schema coverage is already 100%, so the baseline is 3. The description adds genuine meaning beyond the schema by expanding query to include tags, server id, and capability id as acceptable forms, which the schema's 'natural language or keyword query' line does not convey. The limit parameter remains fully covered by its schema description.
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 identifies the exact action ('Search'), the resource ('every indexed downstream MCP capability'), and the query dimensions (natural language, keywords, tags, server id, capability id), which clearly differentiates it from search_servers and the other sibling tools. It also specifies the return nature ('lightweight metadata only'), leaving no ambiguity about what the tool is for.
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 scope phrasing implies when to use it—whenever you need to discover a capability across indexed downstream MCPs—but it never explicitly states when not to use it or points to describe_capabilities/execute_capability/search_servers. Sibling names hint at those alternatives, but the description itself provides no routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_serversSearch serversA
Rank configured downstream MCP servers against a domain-level query. Useful before drilling into capability search.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Domain-level query such as 'project management' |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the core behavior (ranking servers, not modifying them) and the scoping to configured downstream MCP servers. It doesn't cover details like ranking criteria, read-only guarantees, or response shape, but the disclosed behavior is accurate and non-contradictory.
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?
Two short sentences with no filler. The core action is front-loaded, and the usage context is a single additional clause that earns its place.
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?
For a single-parameter search tool with no output schema, the description is largely complete: it states what is ranked, the query type, and when to use it. The main gap is the absence of any mention of the return value, which the absence of an output schema makes slightly more relevant.
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%, and the query parameter is already documented in the schema. The description reinforces 'domain-level query' but adds no parameter format or constraints beyond the schema, so the baseline 3 applies.
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?
Description uses a specific verb ('Rank'), a specific resource ('configured downstream MCP servers'), and a clear scope ('domain-level query'). It also positions itself against the capability-search siblings, so an agent can distinguish it from search_capabilities without opening the schema.
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?
Description gives explicit temporal guidance: use this before drilling into capability search. It doesn't explicitly name the alternative or list when-not-to-use cases, but the context is clear enough given sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
v0.10.0- First observed
describe_capabilities - First observed
execute_capability - First observed
search_capabilities - First observed
search_servers
TDQS
Scored across 4 tools
Each tool has a clear operational role: searching servers, searching capabilities, describing schemas, and executing. search_servers and search_capabilities are adjacent but their descriptions clearly separate domain-level server ranking from capability-level search.
All tool names follow a consistent verb_noun snake_case pattern. The only minor inconsistency is 'capabilities' being plural in search/describe but singular in execute_capability.
Four tools is well-scoped for a gateway or meta-server: discover servers, discover capabilities, inspect schemas, and execute. There is no redundancy or unnecessary bloat.
The discover → describe → execute workflow is covered end-to-end. Minor gaps such as explicit list-all-server or dedicated server metadata retrieval are missing, but search_servers can largely cover discovery needs.
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