eiu-mcp-server
eiu-mcp-server
Сервер на базе Model Context Protocol, который даёт Claude (или любому MCP-совместимому LLM-клиенту) структурированный и эффективный по токенам доступ к API данных EIU — около 200 стран и 320 рядов экономических показателей, включая исторические данные и прогнозы.
Он предоставляет три инструмента:
Инструмент | Назначение |
| Список доступных географий и рядов, с возможностью фильтрации по ключевому слову |
| Поиск по ключевому слову в каталоге рядов (например, |
| Получение данных по коду страны и ряда, с фильтрами по частоте и датам |
Справочные данные загружаются один раз за сессию и кэшируются в памяти, поэтому просмотр и поиск не требуют дополнительных API-вызовов.
Предварительные требования
Доступ к Developer Portal EIU API. Это не самообслуживание. Напишите на economicssupport@economist.com и запросите доступ к Developer Portal. Они вручную создадут вашу учётную запись. Вам понадобятся все три элемента: адрес электронной почты портала, пароль портала и API-ключ, указанный на портале.
На вашей машине должен быть установлен
uv. Одна команда:curl -LsSf https://astral.sh/uv/install.sh | sh
Вам не нужно клонировать этот репозиторий или создавать виртуальное окружение — uvx берёт на себя всё, начиная с git-URL.
Related MCP server: EODHD MCP Server
Установка
Claude Code
Установка одной командой, выполненной из папки, чей .env содержит ваши три значения EIU.
Оболочка читает их, поэтому учётные данные никогда не появятся в вашем диалоге:
set -a; source .env; set +a
claude mcp add --scope user eiu \
-e EIU_API_KEY="$EIU_API_KEY" \
-e EIU_EMAIL="$EIU_EMAIL" \
-e EIU_PASSWORD="$EIU_PASSWORD" \
-- uvx --from git+https://github.com/joshua-bailey/eiu-mcp-server.git eiu-mcp-serverЛибо добавьте запись в .mcp.json вручную:
{
"mcpServers": {
"eiu": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/joshua-bailey/eiu-mcp-server.git",
"eiu-mcp-server"
],
"env": {
"EIU_API_KEY": "${EIU_API_KEY}",
"EIU_EMAIL": "${EIU_EMAIL}",
"EIU_PASSWORD": "${EIU_PASSWORD}"
}
}
}
}Затем перезапустите Claude Code. Три инструмента eiu_* должны появиться в разделе /mcp.
Claude Desktop
Тот же фрагмент JSON, размещённый в разделе mcpServers в:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Claude Desktop не раскрывает ссылки ${VAR}, поэтому впишите туда буквальные значения.
Фиксация версии
По умолчанию uvx устанавливает последний коммит в ветке main. Чтобы зафиксировать конкретный тегированный релиз, добавьте @<tag> к git-URL, например:
"git+https://github.com/joshua-bailey/eiu-mcp-server.git@v0.1.0"Переменные окружения
Переменная | Обязательная? | Назначение |
| Да | Ваш API-ключ EIU из Developer Portal. |
| Да | Адрес электронной почты вашей учётной записи на портале. |
| Да | Пароль от портала. |
Нужны все три. Сервер выполняет вход с помощью адреса электронной почты и пароля, чтобы получить bearer-токен, а затем отправляет этот токен вместе с API-ключом в каждом запросе. Токен кэшируется в памяти и обновляется до истечения срока действия.
Использование
После регистрации MCP спрашивайте у Claude, например:
«Search EIU for current account balance series»
«What EIU series codes cover consumer prices?»
«Pull EIU annual GDP growth (DGDP) for the US, UK and China from 2015 to 2030»
«Show me EIU quarterly inflation forecasts for Brazil, Mexico and Chile»
Claude выберет нужный инструмент и вызовет его.
Коды
Географии — двухбуквенные коды ISO в верхнем регистре:
US,GB,CN,BR.Ряды — собственные короткие коды EIU в верхнем регистре, например
DGDP,DCPI. Используйтеeiu_searchилиeiu_browse, чтобы найти их, а не угадывать.Частота — одно из значений
Yearly,QuarterlyилиMonthly.
eiu_get_data ограничивает ответ 200 точками данных для экономии токенов и сообщает об этом при усечении. Сузьте диапазон дат или список стран, чтобы увидеть остальное.
Справочник по API
Базовый API описан в документации на
developer.eiu.com/help/overview.
Сервер обращается к https://api.eiu.com/v1.
Лицензия
MIT — см. LICENSE. Применяется только к коду обёртки в этом репозитории. Зависимости сохраняют свои собственные лицензии. Данные EIU являются платной подпиской, и их условия использования действуют независимо от данной обёртки.
Available Tools
3 toolseiu_browseA
Browse available EIU geographies and data series.
Call with no filter to see all available geographies/series. Use filter to narrow results by keyword.
Args: filter: Optional keyword (e.g. 'Brazil', 'GDP', 'inflation') show: 'geographies', 'series', or 'both' (default)
| Name | Required | Description | Default |
|---|---|---|---|
| show | No | both | |
| filter | No |
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 carries the behavioral burden. It explains what happens with no filter versus with a filter and describes the show options. It does not mention output format or pagination, but the presence of an output schema reduces the need for that detail.
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: a summary line, short usage guidance, and a clean args list. Every sentence contributes value, with no repetition or filler.
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 browse tool, the description is complete. It covers all parameters, defaults, and core behavior, and the output schema exists to document return values. The lack of explicit sibling routing is the only minor omission, but the intended use is clear.
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 0%, and the description fully compensates. It defines filter as an optional keyword with concrete examples, and show as selecting 'geographies', 'series', or 'both' with the default noted. This is meaningful semantic content beyond 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 opens with a specific verb and resource: 'Browse available EIU geographies and data series.' This clearly distinguishes it from siblings like eiu_get_data and eiu_search, which presumably retrieve or search data rather than browse the catalog.
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 gives clear operational context: 'Call with no filter to see all available geographies/series. Use filter to narrow results by keyword.' It explains how to use the tool and the effect of each parameter, though it does not explicitly state when to prefer eiu_search or eiu_get_data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
eiu_get_dataA
Fetch EIU forecast/indicator data by country and series codes.
Use eiu_browse or eiu_search first to find valid codes.
Args: geography_codes: ISO 2-char codes (e.g. ['US', 'BR', 'CN']) series_codes: EIU series codes (e.g. ['DGDP', 'DCPI']) frequency: 'Yearly', 'Quarterly', or 'Monthly' min_date: Start date YYYY-MM-DD (default: 5 years ago) max_date: End date YYYY-MM-DD (default: 5 years ahead)
| Name | Required | Description | Default |
|---|---|---|---|
| max_date | No | ||
| min_date | No | ||
| frequency | No | Quarterly | |
| series_codes | Yes | ||
| geography_codes | 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 provided, the description carries the full burden. It clearly implies a read-only fetch operation, states the prerequisite of finding valid codes first, and documents default date ranges and accepted frequency values. It could add error/rate-limit behavior, but the default date behavior and non-destructive nature are usefully conveyed.
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-structured. The high-level purpose is front-loaded, the prerequisite is stated in a single sentence, and the Args block is clean and easy to scan. No sentence is wasted or redundant.
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 has an output schema, return-value documentation is not needed. The description covers all five parameters, provides valid examples, explains the required discovery workflow, and states defaults. Everything an agent needs to invoke the tool correctly is present.
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 0%, so the description fully compensates. It explains every parameter: ISO 2-char geography codes with examples, EIU series codes with examples, allowed frequency values, and date format/defaults for min_date and max_date. This is far beyond 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 uses a specific verb ('Fetch') and a specific resource ('EIU forecast/indicator data') with clear scope by country and series codes. This distinguishes it well from the sibling tools eiu_browse and eiu_search, which are for finding codes rather than retrieving data.
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?
It explicitly explains the intended workflow: use eiu_browse or eiu_search first to find valid codes, then call this tool. This is clear guidance on when to use this tool versus the alternatives, leaving no ambiguity for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
eiu_searchA
Search EIU series by keyword in cached reference data.
Use this to find series codes before calling eiu_get_data.
Args: query: Search terms (e.g. 'GDP', 'consumer prices', 'exchange rate') limit: Max results (default 25, max 100)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | 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 is the only source of behavioral context. It adds useful facts about cached reference data and the limit cap (max 100) beyond the schema, but it does not state read-only behavior, output characteristics, or error handling. Acceptable for a simple read-oriented search, but it is not rich.
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 front-loaded: a one-sentence purpose, a clear usage pointer, and a compact Args block. No redundant wording or filler; every sentence contributes.
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 tool is simple, has an output schema to cover return values, and the description provides param details plus sequencing with eiu_get_data. It is slightly incomplete in not addressing the relationship to eiu_browse, but it contains the essential context for correct invocation.
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 0%, but the description compensates by explaining both parameters: query with concrete examples and limit with default and max. It adds meaning beyond the schema, though it could be more precise about the interpretation of 'limit' (number of results vs. something else).
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 states a clear verb and resource: search EIU series by keyword in cached reference data. It also notes the downstream use (finding series codes before calling eiu_get_data), but it does not explicitly differentiate from the sibling eiu_browse, so purpose is clear but sibling distinction is left implicit.
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 gives explicit guidance: 'Use this to find series codes before calling eiu_get_data.' This establishes when to use the tool relative to eiu_get_data, but it does not mention alternatives such as eiu_browse or exclusions, so it falls short of full when/when-not coverage.
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.
3 tool updates
v0.1.0- First observed
eiu_browse - First observed
eiu_get_data - First observed
eiu_search
TDQS
Scored across 3 tools
eiu_browse and eiu_search both support keyword-based series discovery, so agents may be unsure which to call when looking up series codes. eiu_browse is broader because it also covers geographies, while eiu_search is narrowly focused on series, but the boundary is somewhat blurred. eiu_get_data is clearly distinct.
All tools share the eiu_ prefix and use lower_snake_case, making the naming pattern predictable. However, eiu_browse and eiu_search are bare verbs while eiu_get_data is verb_noun, which is a minor inconsistency.
Three tools is a reasonable, compact set for a browse/search/fetch data workflow. The count is appropriate, though eiu_browse and eiu_search overlap enough that the set could arguably be reduced to two tools.
The core workflow of discovering geographies and series, then fetching EIU data, is covered without dead ends. Minor gaps exist around metadata details or available date ranges, but agents can complete the primary task effectively.
Maintenance
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