Executes OpenSearch DSL queries and returns synthesized output (table, list, summary, compact JSON) instead of raw JSON, supporting all query types including aggregations, nested queries, and has_parent queries.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Insights Proxy Show my top 10 most engaged posts from last week"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Context-efficient MCP server that executes OpenSearch queries and returns synthesized output instead of raw JSON.
Full query flexibility, synthesized output only.
You retain 100% of OpenSearch DSL capabilities. The proxy only transforms the output.
┌──────────────────────────────────────────────────────────────────────────┐
│ BEFORE (direct OpenSearch MCP) │
│ Query → OpenSearch → 500+ lines raw JSON → Context window 💥 │
├──────────────────────────────────────────────────────────────────────────┤
│ AFTER (this proxy) │
│ Query → Proxy → OpenSearch → Proxy formats → 20-50 lines → Context ✅ │
└──────────────────────────────────────────────────────────────────────────┘Related MCP server: MCP of MCPs
v1 (Limited) | v2 (Full Flexibility) |
5-6 predefined tools | 1 main tool accepting ANY DSL |
Hardcoded query patterns | You build the query |
Limited aggregations | ALL aggregations supported |
No nested/has_parent | Full query DSL support |
cd mcp-insights-proxy
npm install
npm run buildClaude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"insights-proxy": {
"command": "node",
"args": ["/absolute/path/to/mcp-insights-proxy/dist/index.js"],
"env": {
"OPENSEARCH_URL": "https://your-cluster:9200",
"OPENSEARCH_INDEX": "channel_posts",
"OPENSEARCH_USER": "username",
"OPENSEARCH_PASS": "password"
}
}
}
}opensearch_query (Main Tool)Execute any OpenSearch DSL query. Full flexibility.
Parameters:
Parameter | Type | Description |
| object | Required. Full OpenSearch DSL query object |
| string | Index name (default: |
| enum |
|
| number | Max hits to show (default: 20, max: 50) |
Example - Complex aggregation with nested sub-aggs:
{
"query": {
"size": 0,
"query": {
"bool": {
"must": [
{"term": {"join_field": "post"}},
{"term": {"channel.type": "ig"}}
],
"filter": [
{"range": {"published_at": {"gte": "now-30d"}}}
]
}
},
"aggs": {
"by_hashtag": {
"terms": {"field": "hashtags", "size": 10},
"aggs": {
"avg_engagement": {"avg": {"field": "engagement"}},
"top_creators": {"terms": {"field": "channel.name", "size": 3}}
}
}
}
}
}Example - has_parent query:
{
"query": {
"query": {
"bool": {
"must": [
{"term": {"join_field": "post"}},
{
"has_parent": {
"parent_type": "channel",
"query": {
"bool": {
"must": [
{"term": {"channel.geo.country.code": "IT"}},
{"range": {"channel.followers": {"gte": 100000}}}
]
}
}
}
}
]
}
},
"sort": [{"engagement": "desc"}],
"size": 10,
"_source": ["channel.name", "engagement", "published_at"]
}
}opensearch_countQuick count without full query overhead.
{
"query": {
"bool": {
"must": [
{"term": {"join_field": "post"}},
{"term": {"hashtags": "skincare"}}
]
}
}
}opensearch_mappingGet field list for an index.
auto (default)Automatically detects:
Aggregation-only → summary format
Few hits (≤5) → list format
Many hits → table format
table| # | name | type | engagement | likes | published_at |
|---|------|------|------------|-------|--------------|
| 1 | creator1 | IG | 156K | 142K | 2025-01-15 |
| 2 | creator2 | TT | 98K | 89K | 2025-01-18 |list**1.** @creator1 (IG) • eng: 156K • likes: 142K • views: 2.3M • 2025-01-15
**2.** @creator2 (TT) • eng: 98K • likes: 89K • views: 1.8M • 2025-01-18summaryJust counts and aggregation results, no individual hits.
compact_jsonMinimal JSON with only _source (no _id, _score, _index metadata).
**by_platform:**
• ig: 45.2K
• tt: 32.1K
• yt: 12.8K**engagement_stats:** count=89.1K avg=2.3K min=0 max=1.2M sum=205M**by_hashtag:**
• **skincare** (12.4K)
**avg_engagement:** 3.2K
**top_creators:**
• creator1: 342
• creator2: 287
• **beauty** (8.7K)
**avg_engagement:** 2.8K
...Query Type | Raw JSON | Proxy Output | Savings |
Top 10 posts | ~3000 tokens | ~300 tokens | 90% |
Aggregation (5 buckets) | ~1500 tokens | ~150 tokens | 90% |
Complex nested agg | ~5000 tokens | ~400 tokens | 92% |
Variable | Required | Default | Description |
| Yes |
| Cluster URL |
| No |
| Default index |
| No | - | Basic auth username |
| No | - | Basic auth password |
npm run dev # Development with auto-reload
npm run build # Build for production
npm start # Run production build┌─────────────┐ ┌────────────────────────────────────────────┐ ┌────────────┐
│ │ │ MCP Insights Proxy │ │ │
│ Claude │────▶│ 1. Receive DSL query (any complexity) │────▶│ OpenSearch │
│ (builds │ │ 2. Execute against cluster │ │ │
│ full │◀────│ 3. Parse response │◀────│ │
│ DSL) │ │ 4. Format: table/list/summary │ │ │
│ │ │ 5. Return compact markdown │ │ │
└─────────────┘ └────────────────────────────────────────────┘ └────────────┘
│ │
│ Returns:
│ "*45.2K hits • took 23ms*
│
│ ## Aggregations
│ **by_platform:**
│ • ig: 45.2K
│ • tt: 32.1K
│
│ ## Results
│ | # | name | engagement |..."
│
└─── ~300 tokens instead of ~3000MIT
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