Schema | Fast Context MCP

Fast Context MCP

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Server Configuration

Describes the environment variables required to run the server.

Name	Required	Description	Default
`WS_MODEL`	No	Windsurf model name	MODEL_SWE_1_6_FAST
`WS_LS_VER`	No	Windsurf language server version (protocol metadata)	1.9544.35
`WS_APP_VER`	No	Windsurf app version (protocol metadata)	1.48.2
`FC_MAX_TURNS`	No	Search rounds per query (more = deeper but slower)	3
`FC_TIMEOUT_MS`	No	Connect-Timeout-Ms for streaming requests	30000
`FC_MAX_COMMANDS`	No	Max parallel commands per round	8
`WINDSURF_API_KEY`	No	Windsurf API key. If omitted, the server auto-discovers it from your local Windsurf installation.
`FC_LINE_MAX_CHARS`	No	Max characters per output line (truncation)	250
`FC_RESULT_MAX_LINES`	No	Max lines per command output (truncation)	50

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": true }

Tools

Functions exposed to the LLM to take actions

Name	Description
fast_context_searchA	AI-driven semantic code search using Windsurf's Devstral model. Searches a codebase with natural language and returns relevant file paths with line ranges, plus suggested grep keywords for follow-up searches. Parameter tuning guide: tree_depth: Controls how much directory structure the remote AI sees before searching. If you get a payload/size error, REDUCE this value. If search results are too shallow (missing files in deep subdirectories), INCREASE this value. max_turns: Controls how many search-execute-feedback rounds the remote AI gets. If results are incomplete or the AI didn't find enough files, INCREASE this value. If you want a quick rough answer, use 1. Response includes a [config] line showing actual parameters used — use this to decide adjustments on retry.
extract_windsurf_keyA	Extract Windsurf API Key from local installation. Auto-detects OS (macOS/Windows/Linux) and reads the API key from Windsurf's local database. Set the result as WINDSURF_API_KEY env var.

Name

Description

fast_context_searchA

AI-driven semantic code search using Windsurf's Devstral model. Searches a codebase with natural language and returns relevant file paths with line ranges, plus suggested grep keywords for follow-up searches. Parameter tuning guide:

tree_depth: Controls how much directory structure the remote AI sees before searching. If you get a payload/size error, REDUCE this value. If search results are too shallow (missing files in deep subdirectories), INCREASE this value.
max_turns: Controls how many search-execute-feedback rounds the remote AI gets. If results are incomplete or the AI didn't find enough files, INCREASE this value. If you want a quick rough answer, use 1. Response includes a [config] line showing actual parameters used — use this to decide adjustments on retry.

extract_windsurf_keyA

Extract Windsurf API Key from local installation. Auto-detects OS (macOS/Windows/Linux) and reads the API key from Windsurf's local database. Set the result as WINDSURF_API_KEY env var.

Prompts

Interactive templates invoked by user choice

Name	Description
No prompts

Resources

Contextual data attached and managed by the client

Name	Description
No resources

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.3/5.0

Scored 2026-08-07 07:25 across 2 tools

Disambiguation5/5

The two tools serve completely distinct purposes: one performs AI-powered code search, and the other extracts an API key. There is no overlap or ambiguity between them.

Naming Consistency4/5

Both tools use snake_case and follow a descriptive noun-verb pattern (fast_context_search, extract_windsurf_key). The naming is mostly consistent, though one is more of an adjective_noun_verb while the other is a clear verb_noun.

Tool Count3/5

With only two tools, the server feels thin for its purpose. However, it is narrowly focused on AI-driven search, and each tool is substantial, so the count is borderline acceptable.

Completeness4/5

The core search workflow is covered by the search tool, which includes configurable parameters for depth and turns. The key extraction is a necessary setup step. There are no obvious dead ends, though a few extra utilities (e.g., search history or config management) could enhance completeness.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

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