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Integrations · Model Context Protocol

Complete observability & guardrails for Model Context Protocol (MCP)

Anthropic's Model Context Protocol (MCP) is the universal standard for connecting AI models to tools and data sources. Splyntra provides native MCP client/server telemetry, tool payload auditing, latency profiling, and runtime threat isolation.

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mcp_tracer.py
python
from splyntra.mcp import trace_mcp_server, MCPGuard

# Instrument local or remote MCP servers (stdio / SSE)
server = trace_mcp_server(
    server_name="postgres-analytics-mcp",
    guardrail=MCPGuard(
        deny_destructive_queries=True,
        max_payload_bytes=65536
    )
)

# Every MCP tool discovery and tool invocation is traced
server.start()
Stdio + SSE
Protocol Transports
Full coverage of local & remote MCP connections.
Tool Schemas
Schema Auditing
Validates JSON-RPC schemas and signatures.
< 1ms
Proxy Interceptor
Zero lag inline security inspection.
Audit Log
Immutable Trail
Every MCP tool return saved to the Audit Ledger.

Engineered for high-throughput autonomous agents

Every capability is built into the OpenTelemetry streaming pipeline with sub-millisecond ingestion overhead.

01MCP Telemetry

MCP Client & Server Tool Call Telemetry

Trace JSON-RPC tool discoveries, resource queries, and prompt template calls exchanged between AI models and MCP servers.

  • ✓Transport-level latency profiling (stdio pipes vs HTTP/SSE endpoints)
  • ✓Captures tool execution status, parameters, and returned content blocks
  • ✓Identifies flaky MCP servers and connection resets
02MCP Guard

MCP Tool Sandboxing & Permission Boundaries

Enforce strict security boundaries on what actions MCP servers are permitted to execute in production environments.

  • ✓Block dangerous bash/file/database queries from reaching the MCP server
  • ✓DLP scanning on MCP tool responses to prevent exfiltration of internal secrets
  • ✓Human approval required for elevated MCP tool privileges
03Fleet Dashboard

Multi-MCP Server Aggregation & Health

Monitor all connected MCP servers (GitHub, Postgres, Slack, Filesystem, Custom APIs) in a unified health dashboard.

  • ✓Centralized inventory of active MCP tools across your agent fleet
  • ✓Tool utilization frequency and error rate breakdown
  • ✓Cross-server distributed traces linking agent decisions to MCP outputs

Frequently Asked Questions

How do I connect Splyntra with an existing MCP server?▼
You can either wrap your MCP server in Python/Node using our lightweight SDK wrapper or run the Splyntra MCP Sidecar proxy between your AI agent and the MCP server.
Does Splyntra work with Claude Desktop MCP servers?▼
Yes. You can configure Claude Desktop or any MCP-compliant client to send telemetry directly to Splyntra.

Related Platform Features & Guides

ObservabilityTools & Retrieval →GovernanceTrust Policies →IntegrationsFramework Integrations →

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