SAP Ariba MCP Server
SAP Ariba MCPサーバーへようこそ。
はじめに
Related MCP server: caseware-kb
MCPサーバーのローカルでの実行と検査
MCPサーバーをローカルで実行するには、ターミナルを開いて
uv run main.pyと入力します。ターミナルでUvicornが実行されていることを確認できます。次に、もう一つターミナルを開き、
uv run mcp dev main.pyコマンドを入力します。インスペクターが開くので、そのURLをブラウザに貼り付けてください。パラメーターを以下のように設定します -
Transport Type:
STDIOCommand:
UVArguments:
run --with mcp mcp run main.py
次に ⚙️ Configuration を開き、以下のフィールドを入力します -
Inspector Proxy Address:
http://127.0.0.1:6277(スクリーンショットに示されているターミナルで確認できます)Proxy Session Token: ターミナルからセッションIDをコピーして貼り付けます。
接続ボタンをクリックすると、MCPサーバーに接続されます。
resources、prompts、toolsが表示されるので、toolsをクリックして「List Tools」を選択すると、指定したツールを確認できます。get_event_summaryツールを選択し、以下の入力を提供します -doc_id
user
password_adapter
realm
ツールを実行して出力を確認します。
> Conclustion - We have locally tested the MCP server successfully. BTPへのMCPサーバーのデプロイ
MCPサーバー用デスティネーションの設定
リモートデプロイされたMCPサーバーの検査
リモートデプロイされたMCPサーバーを検査しましょう。
ターミナルで検査コマンド
uv run mcp dev main.pyを実行します。インスペクターでパラメーターを以下のように設定します-
Transport Type:
STDIOCommand:
UVArguments:
run --with mcp mcp run main.py
Available Tools
1 toolget_event_summaryB
Retrieve supplier bids for a sourcing event.
Args: doc_id: Document ID (e.g., 'Doc1213131') user: Username (e.g., myuser) password_adapter: Password adapter (e.g., 'myadaptor') realm: Realm name (e.g., 'myrelm')
| Name | Required | Description | Default |
|---|---|---|---|
| user | Yes | ||
| realm | Yes | ||
| doc_id | Yes | ||
| password_adapter | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must shoulder the burden of behavioral disclosure. 'Retrieve' implies a read-only operation, and the credential arguments hint at authentication requirements, but the description does not mention error behavior, side effects, return format, or any special constraints. This is minimal.
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 compact and well organized: one purpose sentence followed by a tidy args block. Every element serves a function, and the examples are efficiently embedded. No filler or redundant content.
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 4-parameter retrieval tool with an output schema available, the description supplies the call parameters and examples, which is decent. However, it omits when-to-use guidance, where credential values come from, and any operational context such as error conditions or required permissions. It is usable but not fully self-contained.
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 provides only property titles with 0% description coverage, so the description's Args block is essential. It labels each parameter and gives concrete examples (e.g., doc_id as 'Doc1213131', password_adapter as 'myadaptor'), which materially helps an agent understand expected values. It does not explain edge cases or validation, but it compensates well for the bare schema.
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 a specific operation: 'Retrieve supplier bids for a sourcing event.' The verb and resource are explicit, though there is a slight mismatch between the tool name ('event summary') and the described output ('supplier bids'). No sibling tools exist, so differentiation isn't possible, but the core purpose is understandable.
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?
No guidance is provided about when to use this tool, what scenarios it applies to, or when to prefer an alternative. The description is purely declarative and provides no context about typical use cases or prerequisites beyond listing required arguments.
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.
1 tool update
v0.1.0- First observed
get_event_summary
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or misselection between tools. The single tool's purpose is clearly defined.
The one tool name (get_event_summary) follows a clear verb_noun pattern and is internally consistent. Since there are no other tools, there are no naming inconsistencies.
A single tool is far too few for a server named 'SAP Ariba MCP Server,' which implies a broad procurement/sourcing domain. This is a significant under-provisioning for the apparent scope.
The tool only retrieves supplier bids for a sourcing event. There are no operations for managing events, suppliers, bids, or any other typical lifecycle actions, making the surface severely incomplete for the stated domain.
Maintenance
Related MCP Connectors
Any REST/SOAP/GraphQL/OData/SQL API as MCP tools for Claude & ChatGPT. 353 connectors: SAP, ERP.
Provides access to Avalara E-Invoicing and Live Reporting APIs for document statuses and compliance
Discover, search, invoke, and rate A2A (Agent-to-Agent) protocol agents.
Document inventory, extraction, summaries and comparison with source quotes and usage billing.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceExposes 48 SAP Ariba APIs as Claude-compatible tools for managing procurement, sourcing, supplier management, and supply chain data. It enables AI agents to interact with contracts, catalogs, and business network transactions through natural language.MIT
- FlicenseNot gradedqualityDmaintenanceEnables querying procurement documents (invoices, purchase orders, shipping orders, inventory reports) via semantic search, order ID lookups, gap analysis, and source excerpt retrieval.-
- FlicenseBqualityDmaintenanceEnables querying ABAP programs, classes, function modules, and other objects from SAP systems with OAuth 2.0 authentication.2-
- AlicenseNot gradedqualityAmaintenanceIntegrates with Runbook to allow listing, reading, searching, creating, and updating documents, as well as managing workflow processes.29 npm2MIT