Which integrations are available for this server?

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.

How do I use MCP Insights Proxy?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. 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.

MCP Insights Proxy

by lele1983

Overview Schema Related Servers Score Discussions

JavaScript

Remote

MCP Insights Proxy v2

Context-efficient MCP server that executes OpenSearch queries and returns synthesized output instead of raw JSON.

Philosophy

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

Key Difference from v1

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

Quick Start

1. Install

cd mcp-insights-proxy
npm install
npm run build

2. Configure MCP Client

Claude 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"
      }
    }
  }
}

3. Restart Claude

Tools

`opensearch_query` (Main Tool)

Execute any OpenSearch DSL query. Full flexibility.

Parameters:

Parameter	Type	Description
`query`	object	Required. Full OpenSearch DSL query object
`index`	string	Index name (default: `channel_posts`)
`output_format`	enum	`auto`, `table`, `list`, `summary`, `compact_json`
`max_display`	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_count`

Quick count without full query overhead.

{
  "query": {
    "bool": {
      "must": [
        {"term": {"join_field": "post"}},
        {"term": {"hashtags": "skincare"}}
      ]
    }
  }
}

`opensearch_mapping`

Get field list for an index.

Output Formats

`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 • 2025-01-18

`summary`

Just counts and aggregation results, no individual hits.

`compact_json`

Minimal JSON with only _source (no _id, _score, _index metadata).

Aggregation Output Examples

Terms aggregation

**by_platform:**
  • ig: 45.2K
  • tt: 32.1K
  • yt: 12.8K

Stats aggregation

**engagement_stats:** count=89.1K avg=2.3K min=0 max=1.2M sum=205M

Nested sub-aggregations

**by_hashtag:**
  • **skincare** (12.4K)
    **avg_engagement:** 3.2K
    **top_creators:**
      • creator1: 342
      • creator2: 287
  • **beauty** (8.7K)
    **avg_engagement:** 2.8K
    ...

Context Savings

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%

Environment Variables

Variable	Required	Default	Description
`OPENSEARCH_URL`	Yes	`http://localhost:9200`	Cluster URL
`OPENSEARCH_INDEX`	No	`channel_posts`	Default index
`OPENSEARCH_USER`	No	-	Basic auth username
`OPENSEARCH_PASS`	No	-	Basic auth password

Development

npm run dev    # Development with auto-reload
npm run build  # Build for production
npm start      # Run production build

Architecture

┌─────────────┐     ┌────────────────────────────────────────────┐     ┌────────────┐
│             │     │           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 ~3000

License

MIT

This server cannot be installed

license - not found

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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