Glossary

Context Bloat

Context bloat is the accumulation of tokens in an LLM's context window before the user has asked anything — usually from MCP tool schemas, large system prompts, or unfiltered retrieval results — that crowds out room for actual reasoning.

Definition

Context bloat is the accumulation of tokens in an LLM's context window before the user has asked anything — usually from MCP tool schemas, large system prompts, or unfiltered retrieval results — that crowds out room for actual reasoning.

In Depth

Most agent frameworks load every connected tool's full schema into context at session start. A fleet of 10 MCP servers with 8 tools each at 600 tokens per schema burns 48,000 tokens before any work happens. Context bloat compounds when retrieval steps return raw HTML or 50-result SERP pages instead of trimmed structured snippets. The standard 2026 fixes: MCP gateways that compress tool descriptions, search APIs that return typed JSON instead of raw HTML, and agent harnesses that lazy-load tool schemas only when the model attempts to call them.

Example Usage

Real-World Example

After consolidating to an MCP gateway and switching from raw-HTML scraping to typed Scavio JSON, the agent's per-turn context bloat dropped from 50K tokens to under 8K, freeing room for genuine reasoning.

Platforms

Context Bloat is relevant across the following platforms, all accessible through Scavio's unified API:

  • google

Related Terms

Frequently Asked Questions

Context bloat is the accumulation of tokens in an LLM's context window before the user has asked anything — usually from MCP tool schemas, large system prompts, or unfiltered retrieval results — that crowds out room for actual reasoning.

After consolidating to an MCP gateway and switching from raw-HTML scraping to typed Scavio JSON, the agent's per-turn context bloat dropped from 50K tokens to under 8K, freeing room for genuine reasoning.

Context Bloat is relevant to google. Scavio provides a unified API to access data from all of these platforms.

Most agent frameworks load every connected tool's full schema into context at session start. A fleet of 10 MCP servers with 8 tools each at 600 tokens per schema burns 48,000 tokens before any work happens. Context bloat compounds when retrieval steps return raw HTML or 50-result SERP pages instead of trimmed structured snippets. The standard 2026 fixes: MCP gateways that compress tool descriptions, search APIs that return typed JSON instead of raw HTML, and agent harnesses that lazy-load tool schemas only when the model attempts to call them.

Context Bloat

Start using Scavio to work with context bloat across Google, Amazon, YouTube, Walmart, and Reddit.