mcp-elicitation-proxy
Let existing MCP servers ask for missing required tool arguments through MCP elicitation, without changing the upstream server.
README
mcp-elicitation-proxy
A transparent MCP proxy that adds elicitation for missing required tool arguments while preserving upstream tool discovery and schemas.
mcp-elicitation-proxy is a standalone Python MCP proxy built on FastMCP. It
preserves native upstream tool discovery while adding tool-call middleware for
required-field elicitation and sensitive required-field blocking.
The core architectural rule is strict: upstream discovery stays native. The
proxy must preserve upstream tools/list output instead of replacing it with a
synthetic wrapper such as call_upstream_tool.
Install
Run directly with uvx:
uvx mcp-elicitation-proxy --config config.yaml
For development from a local checkout, use the development setup steps below.
Development Setup
uv sync
Run tests:
uv run pytest -q
Optional lint:
uv run ruff check .
Build artifacts can be produced with uv build. Local outputs under dist/
are not intended to be committed.
Configuration
Example config.yaml with an HTTP upstream:
proxy:
name: "mcp-elicitation-proxy"
upstream:
url: "http://localhost:8001/mcp"
elicitation:
enabled: true
fallback_on_unsupported: "structured_error"
policies:
schema_required:
enabled: true
sensitive_required:
enabled: true
tools:
search_docs:
required:
- query
- project
elicit:
message: "Provide the missing search details."
fields:
project:
type: "string"
description: "Project or scope to search."
Example config.yaml with a command-based upstream:
proxy:
name: "mcp-elicitation-proxy"
upstream:
command: "npx"
args:
- -y
- "@modelcontextprotocol/server-everything"
upstream.url and upstream.command are mutually exclusive. Exactly one must
be configured. upstream.args defaults to an empty list and is valid only with
upstream.command. Command-based upstreams may also provide string environment
variables with upstream.env.
Run the proxy:
uv run mcp-elicitation-proxy --config config.yaml
You can also provide the config path via MCP_ELICITATION_PROXY_CONFIG.
MCP Client Configuration
When configuring an MCP client, use mcp-elicitation-proxy as the package and
CLI command. The local MCP client server alias can be shorter; the recommended
alias is elicitation-proxy.
{
"mcpServers": {
"elicitation-proxy": {
"command": "uvx",
"args": [
"mcp-elicitation-proxy",
"--config",
"/path/to/config.yaml"
]
}
}
}
In this example, elicitation-proxy is only the client-local server alias.
mcp-elicitation-proxy remains the PyPI package name and CLI command. These
names do not need to match. If desired, the proxy's own MCP server name can also
be set separately in YAML:
proxy:
name: "elicitation-proxy"
Discovery Invariants
- Upstream tools remain visible in native
tools/list. - The proxy does not register a generic
call_upstream_tool. - Tool names are not prefixed with values such as
upstream_. - Tool names, descriptions, and input schemas remain the upstream values unless an explicit future discovery feature changes that contract.
The upstream server is delegated to FastMCP native proxying via
fastmcp.server.create_proxy(...).
Required Fields And Elicitation
schema_required uses native upstream JSON Schema required fields.
Per-tool tools.<tool_name>.required entries are added at runtime for
tools/call validation only. Schema-required fields keep their original order,
then configured fields are appended without duplicates.
When elicitation.enabled is true, missing non-sensitive required fields may
be requested with the client's MCP elicitation capability and merged into the
original arguments before forwarding upstream. If elicitation is disabled,
unsupported, declined, cancelled, or fails, the proxy returns a structured
result instead of calling the upstream tool.
The sensitive_required policy runs before normal required-field elicitation.
If a missing required field appears to be a credential or secret, the proxy
blocks form-mode elicitation and returns a structured tool_call_blocked
result. Complete explicit input is still forwarded.
ambiguous_if and confirm_if settings are parsed for forward-compatible
configuration, but advanced ambiguity, confirmation, and LLM-based policies are
not implemented in v0.1.0.
Manual Smoke Test With MCP Inspector
A repeatable manual test is available with MCP Inspector and the official
@modelcontextprotocol/server-everything reference server.
npx @modelcontextprotocol/inspector -- uv run mcp-elicitation-proxy --config examples/manual-everything.config.yaml
This test verifies command-based upstream startup, native upstream tool
discovery, forwarding, elicitation for missing required fields,
sensitive-required blocking, and upstream.env propagation.
Expected high-level checks:
echois visible as an upstream tool;call_upstream_toolis not present;- tool names are not prefixed with
upstream_; - calling
echowith a completemessageis forwarded; - calling
echowithoutmessagetriggers elicitation; - configured elicitation copy from
examples/manual-everything.config.yamlis used; - marking a missing required field as sensitive blocks elicitation;
- the configured environment variable is visible to the upstream environment tool.
See docs/manual-inspector-test.md for details.
Status
v0.1.0 is the first public-ready baseline. It includes a single-upstream
FastMCP proxy, native discovery preservation, required-field elicitation,
sensitive required-field blocking, command-based upstream startup, YAML
configuration, and automated coverage for the main proxy invariants.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。